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            "name": "BetAware",
            "description": "A software package for the analysis of TransMembrane β-barrel proteins.",
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                            "term": "Protein secondary structure prediction"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0269",
                            "term": "Transmembrane protein prediction"
                        }
                    ],
                    "input": [
                        {
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                                "uri": "http://edamontology.org/data_2974",
                                "term": "Protein sequence (raw)"
                            },
                            "format": [
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                                    "term": "FASTA"
                                }
                            ]
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                    "note": "Prediction",
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                "Web application"
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                {
                    "uri": "http://edamontology.org/topic_0082",
                    "term": "Structure prediction"
                },
                {
                    "uri": "http://edamontology.org/topic_3542",
                    "term": "Protein secondary structure"
                }
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                    "url": "http://betaware.biocomp.unibo.it/BetAware/default/software",
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                    "url": "http://bioinformatics.oxfordjournals.org/content/29/4/504.abstract",
                    "type": [
                        "Citation instructions"
                    ],
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                },
                {
                    "url": "http://betaware.biocomp.unibo.it/BetAware/default/software",
                    "type": [
                        "Command-line options"
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            ],
            "publication": [
                {
                    "doi": "10.1093/bioinformatics/bts728",
                    "pmid": "23297037",
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                    "version": null,
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                    "metadata": {
                        "title": "BETAWARE: A machine-learning tool to detect and predict transmembrane beta-barrel proteins in prokaryotes",
                        "abstract": "The annotation of membrane proteins in proteomes is an important problem of Computational Biology, especially after the development of high-throughput techniques that allow fast and efficient genome sequencing. Among membrane proteins, transmembrane β-barrels (TMBBs) are poorly represented in the database of protein structures (PDB) and difficult to identify with experimental approaches. They are, however, extremely important, playing key roles in several cell functions and bacterial pathogenicity. TMBBs are included in the lipid bilayer with a β-barrel structure and are presently found in the outer membranes of Gram-negative bacteria, mitochondria and chloroplasts. Recently, we developed two top-performing methods based on machine-learning approaches to tackle both the detection of TMBBs in sets of proteins and the prediction of their topology. Here, we present our BETAWARE program that includes both approaches and can run as a standalone program on a linux-based computer to easily address in-home massive protein annotation or filtering.Availability and implementation: http://www.biocomp.unibo.it/ ∼savojard/betawarecl. © 2013 The Author.",
                        "date": "2013-02-15T00:00:00Z",
                        "citationCount": 38,
                        "authors": [
                            {
                                "name": "Savojardo C."
                            },
                            {
                                "name": "Fariselli P."
                            },
                            {
                                "name": "Casadio R."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                },
                {
                    "doi": "10.1093/bioinformatics/btr549",
                    "pmid": null,
                    "pmcid": null,
                    "type": [
                        "Other"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Improving the detection of transmembrane β-barrel chains with N-to-1 extreme learning machines",
                        "abstract": "Motivation: Transmembrane β-barrels (TMBBs) are extremely important proteins that play key roles in several cell functions. They cross the lipid bilayer with β-barrel structures. TMBBs are presently found in the outer membranes of Gram-negative bacteria and of mitochondria and chloroplasts. Loop exposure outside the bacterial cell membranes makes TMBBs important targets for vaccine or drug therapies. In genomes, they are not highly represented and are difficult to identify with experimental approaches. Several computational methods have been developed to discriminate TMBBs from other types of proteins. However, the best performing approaches have a high fraction of false positive predictions.Results: In this article, we introduce a new machine learning approach for TMBB detection based on N-to-1 Extreme Learning Machines that significantly outperforms previous methods achieving a Matthews correlation coefficient of 0.82, a probability of correct prediction of 0.92 and a sensitivity of 0.73. © The Author 2011. Published by Oxford University Press. All rights reserved.",
                        "date": "2011-11-01T00:00:00Z",
                        "citationCount": 19,
                        "authors": [
                            {
                                "name": "Savojardo C."
                            },
                            {
                                "name": "Fariselli P."
                            },
                            {
                                "name": "Casadio R."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                },
                {
                    "doi": "10.1186/1748-7188-4-13",
                    "pmid": null,
                    "pmcid": null,
                    "type": [
                        "Other"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Grammatical-restrained hidden conditional random fields for bioinformatics applications",
                        "abstract": "Background: Discriminative models are designed to naturally address classification tasks. However, some applications require the inclusion of grammar rules, and in these cases generative models, such as Hidden Markov Models (HMMs) and Stochastic Grammars, are routinely applied. Results: We introduce Grammatical-Restrained Hidden Conditional Random Fields (GRHCRFs) as an extension of Hidden Conditional Random Fields (HCRFs). GRHCRFs while preserving the discriminative character of HCRFs, can assign labels in agreement with the production rules of a defined grammar. The main GRHCRF novelty is the possibility of including in HCRFs prior knowledge of the problem by means of a defined grammar. Our current implementation allows regular grammar rules. We test our GRHCRF on a typical biosequence labeling problem: the prediction of the topology of Prokaryotic outer-membrane proteins. Conclusion: We show that in a typical biosequence labeling problem the GRHCRF performs better than CRF models of the same complexity, indicating that GRHCRFs can be useful tools for biosequence analysis applications. Availability: GRHCRF software is available under GPLv3 licence at the website. http://www.biocomp.unibo.it/~savojard/biocrf-0.9.tar.gz. © 2009 Fariselli et al; licensee BioMed Central Ltd.",
                        "date": "2009-10-22T00:00:00Z",
                        "citationCount": 18,
                        "authors": [
                            {
                                "name": "Fariselli P."
                            },
                            {
                                "name": "Savojardo C."
                            },
                            {
                                "name": "Martelli P.L."
                            },
                            {
                                "name": "Casadio R."
                            }
                        ],
                        "journal": "Algorithms for Molecular Biology"
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                }
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                },
                {
                    "name": "Castrense Savojardo",
                    "email": "castrense.savojardo2@unibo.it",
                    "url": "http://biocomp.unibo.it/savojard/",
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            "name": "hictk",
            "description": "Blazing fast toolkit to work with .hic and .cool files",
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                            "term": "Analysis"
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                            "term": "Alignment"
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                    "term": "Biology"
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                    "term": "Omics"
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                    "note": "Ben-ben Miao, Wei Dong, Yi-xin Gu, Zhao-fang Han, Xuan Luo, Cai-huan Ke, Wei-wei You, OmicsSuite: a customized and pipelined suite for analysis and visualization of multi-omics big data, Horticulture Research, 2023;, uhad195, https://doi.org/10.1093/hr/uhad195.",
                    "metadata": {
                        "title": "OmicsSuite: a customized and pipelined suite for analysis and visualization of multi-omics big data",
                        "abstract": "With the advancements in high-throughput sequencing technologies such as Illumina, PacBio, and 10X Genomics platforms, and gas/liquid chromatography-mass spectrometry, large volumes of biological data in multiple formats can now be obtained through multi-omics analysis. Bioinformatics is constantly evolving and seeking breakthroughs to solve multi-omics problems; however, it is challenging for most experimental biologists to analyse data using command-line interfaces, coding, and scripting. Based on experience with multi-omics, we have developed OmicsSuite, a desktop suite that comprehensively integrates statistics and multi-omics analysis and visualization. The suite has 175 sub-applications in 12 categories, including Sequence, Statistics, Algorithm, Genomics, Transcriptomics, Enrichment, Proteomics, Metabolomics, Clinical, Microorganism, Single Cell, and Table Operation. We created the user interface with Sequence View, Table View, and intelligent components based on JavaFX and the popular Shiny framework. The multi-omics analysis functions were developed based on BioJava and 300+ packages provided by the R CRAN and Bioconductor communities, and it encompasses over 3000 adjustable parameter interfaces. OmicsSuite can directly read multi-omics raw data in FastA, FastQ, Mutation Annotation Format, mzML, Matrix, and HDF5 formats, and the programs emphasize data transfer directions and pipeline analysis functions. OmicsSuite can produce pre-publication images and tables, allowing users to focus on biological aspects. OmicsSuite offers multi-omics step-by-step workflows that can be easily applied to horticultural plant breeding and molecular mechanism studies in plants. It enables researchers to freely explore the molecular information contained in multi-omics big data (Source: https://github.com/OmicsSuite/, Website: https://omicssuite.github.io, v1.3.9).",
                        "date": "2023-11-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Miao B.-B."
                            },
                            {
                                "name": "Dong W."
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                            {
                                "name": "Gu Y.-X."
                            },
                            {
                                "name": "Han Z.-F."
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                            {
                                "name": "Luo X."
                            },
                            {
                                "name": "Ke C.-H."
                            },
                            {
                                "name": "You W.-W."
                            }
                        ],
                        "journal": "Horticulture Research"
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                        "title": "A Deeper Look into Comet - Implementation and Features",
                        "abstract": "The Comet database search software was initially released as an open source project in late 2012. Prior to that, Comet existed as the University of Washington's academic version of the SEQUEST database search tool. Despite its availability and widespread use over the years, some details about its implementation have not been previously disseminated or are not well understood. We address a few of these details in depth and highlight new features available in the latest release. Comet is freely available for download at http://comet-ms.sourceforge.net or it can be accessed as a component of a number of larger software projects into which it has been incorporated. (Figure Presented).",
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                    "metadata": {
                        "title": "Molecular phylogenetics by direct comparison of tandem mass spectra",
                        "abstract": "Rationale: Molecular phylogenetics is the study of evolution and relatedness of organisms or genes. Mass spectrometry is used routinely for bacterial identification and has also been used for phylogenetic analysis, for instance from bone material. Unfortunately, only a small fraction of the acquired tandem mass spectra allow direct interpretation. Methods: We describe a new algorithm and software for molecular phylogenetics using pairwise comparisons of tandem mass spectra from enzymatically digested proteins. The spectra need not be annotated and all acquired data is used in the analysis. To demonstrate the method, we analyzed tryptic digests of sera from four great apes and two other primates. Results: The distribution of spectra dot products for thousands of tandem mass spectra collected from two samples provides a measure on the fraction of shared peptides between the two samples. When inverted, this becomes a distance metric. By pairwise comparison between species and averaging over four individuals per species, it was possible to reconstruct the unique correct phylogenetic tree for the great apes and other primates. Conclusions: The new method described here has several attractive features compared with existing methods, among them simplicity, the unbiased use of all acquired data rather than a small subset of spectra, and the potential use of heavily degraded proteins or proteins with a priori unknown modifications. © 2012 John Wiley & Sons, Ltd.",
                        "date": "2012-04-15T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Palmblad M."
                            },
                            {
                                "name": "Deelder A.M."
                            }
                        ],
                        "journal": "Rapid Communications in Mass Spectrometry"
                    }
                },
                {
                    "doi": "10.1021/acs.jproteome.2c00457",
                    "pmid": "36173614",
                    "pmcid": "PMC9903320",
                    "type": [
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                    "version": "2.0",
                    "note": null,
                    "metadata": {
                        "title": "compareMS2 2.0: An Improved Software for Comparing Tandem Mass Spectrometry Datasets",
                        "abstract": "It has long been known that biological species can be identified from mass spectrometry data alone. Ten years ago, we described a method and software tool, compareMS2, for calculating a distance between sets of tandem mass spectra, as routinely collected in proteomics. This method has seen use in species identification and mixture characterization in food and feed products, as well as other applications. Here, we present the first major update of this software, including a new metric, a graphical user interface and additional functionality. The data have been deposited to ProteomeXchange with dataset identifier PXD034932.",
                        "date": "2023-02-03T00:00:00Z",
                        "citationCount": 2,
                        "authors": [
                            {
                                "name": "Marissen R."
                            },
                            {
                                "name": "Varunjikar M.S."
                            },
                            {
                                "name": "Laros J.F.J."
                            },
                            {
                                "name": "Rasinger J.D."
                            },
                            {
                                "name": "Neely B.A."
                            },
                            {
                                "name": "Palmblad M."
                            }
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                        "journal": "Journal of Proteome Research"
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                {
                    "doi": "10.1021/acs.jproteome.1c00528",
                    "pmid": "34523928",
                    "pmcid": "PMC8491155",
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                    "metadata": {
                        "title": "Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics Experiments in the Light of Proteomics",
                        "abstract": "Science is full of overlooked and undervalued research waiting to be rediscovered. Proteomics is no exception. In this perspective, we follow the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing tryptic peptides across animal species. This pioneering work directly led to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics. In the decades following, proteins continued to provide essential clues on evolutionary history. While technology has continued to improve, contemporary proteomics has strayed from this larger biological context, rarely comparing species or asking how protein structure, function, and interactions have evolved. Here we recombine proteomics with molecular phylogenetics, highlighting the value of framing proteomic results in a larger biological context and how almost forgotten research, though technologically surpassed, can still generate new ideas and illuminate our work from a different perspective. Though it is infeasible to read all research published on a large topic, looking up older papers can be surprisingly rewarding when rediscovering a \"gem\"at the end of a long citation chain, aided by digital collections and perpetually helpful librarians. Proper literature study reduces unnecessary repetition and allows research to be more insightful and impactful by truly standing on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/) as dataset MSV000087993.",
                        "date": "2021-10-01T00:00:00Z",
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                            {
                                "name": "Neely B.A."
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                            {
                                "name": "Palmblad M."
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                        "journal": "Journal of Proteome Research"
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            "description": "Jalview is a free program for multiple sequence alignment editing, visualisation and analysis. Use it to view and edit sequence alignments, analyse them with phylogenetic trees and principal components analysis (PCA) plots and explore molecular structures and annotation.",
            "homepage": "https://www.jalview.org/",
            "biotoolsID": "Jalview",
            "biotoolsCURIE": "biotools:Jalview",
            "version": [
                "2.11.3.2"
            ],
            "otherID": [],
            "relation": [
                {
                    "biotoolsID": "jabaws",
                    "type": "uses"
                },
                {
                    "biotoolsID": "chimera",
                    "type": "uses"
                },
                {
                    "biotoolsID": "chimerax",
                    "type": "uses"
                },
                {
                    "biotoolsID": "pymol",
                    "type": "uses"
                },
                {
                    "biotoolsID": "bioconda",
                    "type": "includedIn"
                },
                {
                    "biotoolsID": "3d-beacons",
                    "type": "uses"
                },
                {
                    "biotoolsID": "uniprot",
                    "type": "uses"
                },
                {
                    "biotoolsID": "pfam",
                    "type": "uses"
                },
                {
                    "biotoolsID": "ensembl",
                    "type": "uses"
                },
                {
                    "biotoolsID": "pdb",
                    "type": "uses"
                },
                {
                    "biotoolsID": "rfam",
                    "type": "uses"
                }
            ],
            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_0564",
                            "term": "Sequence visualisation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0324",
                            "term": "Phylogenetic tree analysis"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3081",
                            "term": "Sequence alignment editing"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0863",
                                "term": "Sequence alignment"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_1939",
                                    "term": "GFF3-seq"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1982",
                                    "term": "ClustalW format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1961",
                                    "term": "Stockholm format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1984",
                                    "term": "FASTA-aln"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1938",
                                    "term": "GFF2-seq"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1929",
                                    "term": "FASTA"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1948",
                                    "term": "nbrf/pir"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3774",
                                    "term": "BioJSON (Jalview)"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1997",
                                    "term": "PHYLIP format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3313",
                                    "term": "BLC"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3311",
                                    "term": "RNAML"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1947",
                                    "term": "GCG MSF"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3015",
                                    "term": "Pileup"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1477",
                                    "term": "mmCIF"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3016",
                                    "term": "VCF"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1915",
                                    "term": "Format"
                                }
                            ]
                        },
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0886",
                                "term": "Structure alignment"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_1476",
                                    "term": "PDB"
                                }
                            ]
                        }
                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0863",
                                "term": "Sequence alignment"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_1948",
                                    "term": "nbrf/pir"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3464",
                                    "term": "JSON"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1961",
                                    "term": "Stockholm format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1929",
                                    "term": "FASTA"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1997",
                                    "term": "PHYLIP format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3313",
                                    "term": "BLC"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3774",
                                    "term": "BioJSON (Jalview)"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1947",
                                    "term": "GCG MSF"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3015",
                                    "term": "Pileup"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1982",
                                    "term": "ClustalW format"
                                }
                            ]
                        },
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_2884",
                                "term": "Plot"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_3603",
                                    "term": "PNG"
                                },
                                {
                                    "uri": "http://edamontology.org/format_2331",
                                    "term": "HTML"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3466",
                                    "term": "EPS"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3604",
                                    "term": "SVG"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1915",
                                    "term": "Format"
                                }
                            ]
                        }
                    ],
                    "note": "Other Input formats:\nAMSA (.amsa);\nJnetFile (.concise, .jnet);\nPFAM (.pfam);\nSubstitution matrix (.matrix);\nJalview Project File (.jvp);\nJalview Feature File (.features, .jvfeatures);\nJalview Annotations File (.annotations, .jvannotations);\nPredicted Aligned Error (PAE) Matrix File (.json)\n...\nOther Output formats:\nPFAM (.pfam);\nBioJS (.biojs) (interactive HTML/Javascript);\nJalview Project File (.jvp);",
                    "cmd": null
                }
            ],
            "toolType": [
                "Desktop application",
                "Command-line tool"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0080",
                    "term": "Sequence analysis"
                },
                {
                    "uri": "http://edamontology.org/topic_0092",
                    "term": "Data visualisation"
                }
            ],
            "operatingSystem": [
                "Linux",
                "Windows",
                "Mac"
            ],
            "language": [],
            "license": "GPL-3.0",
            "collectionID": [
                "ELIXIR-UK"
            ],
            "maturity": "Mature",
            "cost": "Free of charge",
            "accessibility": "Open access",
            "elixirPlatform": [
                "Tools"
            ],
            "elixirNode": [
                "UK"
            ],
            "elixirCommunity": [],
            "link": [
                {
                    "url": "https://discourse.jalview.org/",
                    "type": [
                        "Discussion forum"
                    ],
                    "note": null
                },
                {
                    "url": "https://issues.jalview.org/",
                    "type": [
                        "Issue tracker"
                    ],
                    "note": null
                },
                {
                    "url": "https://www.jalview.org/development/jalview_develop/",
                    "type": [
                        "Other"
                    ],
                    "note": "Latest development version"
                },
                {
                    "url": "https://source.jalview.org/crucible/browse/jalview",
                    "type": [
                        "Repository"
                    ],
                    "note": null
                },
                {
                    "url": "https://twitter.com/Jalview",
                    "type": [
                        "Social media"
                    ],
                    "note": "Twitter feed"
                },
                {
                    "url": "https://www.youtube.com/channel/UCIjpnvZB770yz7ftbrJ0tfw",
                    "type": [
                        "Social media"
                    ],
                    "note": "YouTube training videos"
                }
            ],
            "download": [
                {
                    "url": "https://www.jalview.org/download",
                    "type": "Downloads page",
                    "note": null,
                    "version": null
                },
                {
                    "url": "https://www.jalview.org/download/source/",
                    "type": "Source code",
                    "note": null,
                    "version": null
                },
                {
                    "url": "https://www.jalview.org/download/?os=all",
                    "type": "Binaries",
                    "note": "Binaries for all platforms",
                    "version": null
                },
                {
                    "url": "https://www.jalview.org/favicon.svg",
                    "type": "Icon",
                    "note": null,
                    "version": null
                },
                {
                    "url": "https://www.jalview.org/download/other/jar/",
                    "type": "Binaries",
                    "note": "Executable JAR file",
                    "version": null
                }
            ],
            "documentation": [
                {
                    "url": "https://www.jalview.org/about/citation",
                    "type": [
                        "Citation instructions"
                    ],
                    "note": null
                },
                {
                    "url": "https://www.jalview.org/training/",
                    "type": [
                        "Training material"
                    ],
                    "note": "Hands-on exercises, Training courses and Training videos"
                },
                {
                    "url": "https://www.jalview.org/help/faq",
                    "type": [
                        "FAQ"
                    ],
                    "note": null
                },
                {
                    "url": "https://www.jalview.org/help/documentation/",
                    "type": [
                        "User manual"
                    ],
                    "note": null
                }
            ],
            "publication": [
                {
                    "doi": "10.1093/bioinformatics/btp033",
                    "pmid": null,
                    "pmcid": null,
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Jalview Version 2-A multiple sequence alignment editor and analysis workbench",
                        "abstract": "Summary: Jalview Version 2 is a system for interactive WYSIWYG editing, analysis and annotation of multiple sequence alignments. Core features include keyboard and mouse-based editing, multiple views and alignment overviews, and linked structure display with Jmol. Jalview 2 is available in two forms: a lightweight Java applet for use in web applications, and a powerful desktop application that employs web services for sequence alignment, secondary structure prediction and the retrieval of alignments, sequences, annotation and structures from public databases and any DAS 1.53 compliant sequence or annotation server. © 2009 The Author(s).",
                        "date": "2009-05-07T00:00:00Z",
                        "citationCount": 6231,
                        "authors": [
                            {
                                "name": "Waterhouse A.M."
                            },
                            {
                                "name": "Procter J.B."
                            },
                            {
                                "name": "Martin D.M.A."
                            },
                            {
                                "name": "Clamp M."
                            },
                            {
                                "name": "Barton G.J."
                            }
                        ],
                        "journal": "Bioinformatics"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Jim Procter",
                    "email": null,
                    "url": "http://www.lifesci.dundee.ac.uk/people/jim-procter",
                    "orcidid": "https://orcid.org/0000-0002-7865-7382",
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                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [
                        "Primary contact"
                    ],
                    "note": null
                },
                {
                    "name": "Geoff Barton",
                    "email": null,
                    "url": "https://www.lifesci.dundee.ac.uk/people/geoff-barton",
                    "orcidid": "https://orcid.org/0000-0002-9014-5355",
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": null,
                    "typeRole": [],
                    "note": null
                }
            ],
            "community": null,
            "owner": "ben_s",
            "additionDate": "2019-02-13T17:01:40Z",
            "lastUpdate": "2023-12-01T12:00:21.286261Z",
            "editPermission": {
                "type": "group",
                "authors": [
                    "ben_s",
                    "jimprocter"
                ]
            },
            "validated": 1,
            "homepage_status": 0,
            "elixir_badge": 0,
            "confidence_flag": null
        },
        {
            "name": "PIA - Protein Inference Algorithms",
            "description": "The main focus lays on the integrated inference algorithms, concluding the proteins from a set of identified spectra. But it also allows you to integrate results of various search engines, inspect your peptide spectrum matches, calculate FDR values across different results and visualize the correspondence between PSMs, peptides and proteins.",
            "homepage": "https://github.com/medbioinf/pia",
            "biotoolsID": "pia",
            "biotoolsCURIE": "biotools:pia",
            "version": [
                "1.4"
            ],
            "otherID": [],
            "relation": [
                {
                    "biotoolsID": "knime",
                    "type": "uses"
                }
            ],
            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_2945",
                            "term": "Analysis"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0943",
                                "term": "Mass spectrometry spectra"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_3713",
                                    "term": "Mascot .dat file"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3247",
                                    "term": "mzIdentML"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3475",
                                    "term": "TSV"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3684",
                                    "term": "PRIDE XML"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3711",
                                    "term": "X!Tandem XML"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3702",
                                    "term": "MSF"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3681",
                                    "term": "mzTab"
                                }
                            ]
                        }
                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0945",
                                "term": "Peptide identification"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_2206",
                                    "term": "Sequence feature table format (text)"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3765",
                                    "term": "KNIME datatable format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3764",
                                    "term": "idXML"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3475",
                                    "term": "TSV"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3681",
                                    "term": "mzTab"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3247",
                                    "term": "mzIdentML"
                                }
                            ]
                        },
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0989",
                                "term": "Protein identifier"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_2206",
                                    "term": "Sequence feature table format (text)"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3765",
                                    "term": "KNIME datatable format"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3764",
                                    "term": "idXML"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3475",
                                    "term": "TSV"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3681",
                                    "term": "mzTab"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3247",
                                    "term": "mzIdentML"
                                }
                            ]
                        }
                    ],
                    "note": "PIA allows you to inspect the results of common proteomics spectrum identification search engines, combine them seamlessly and conduct statistical analyses. The main focus of PIA lays on the integrated inference algorithms, i.e. concluding the proteins from a set of identified spectra. But it also allows you to inspect your peptide spectrum matches, calculate FDR values across different search engine results and visualize the correspondence between PSMs, peptides and proteins. Search engine results in several formats peptide spectrum matches (PSMs) and peptides Inferred Proteins",
                    "cmd": null
                }
            ],
            "toolType": [
                "Command-line tool",
                "Library",
                "Desktop application",
                "Workflow"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0121",
                    "term": "Proteomics"
                },
                {
                    "uri": "http://edamontology.org/topic_3520",
                    "term": "Proteomics experiment"
                },
                {
                    "uri": "http://edamontology.org/topic_3120",
                    "term": "Protein variants"
                }
            ],
            "operatingSystem": [
                "Linux",
                "Windows",
                "Mac"
            ],
            "language": [
                "Java"
            ],
            "license": "BSD-3-Clause",
            "collectionID": [
                "KNIME",
                "de.NBI",
                "Proteomics",
                "BioInfra.Prot",
                "CUBiMed.RUB"
            ],
            "maturity": "Mature",
            "cost": "Free of charge",
            "accessibility": "Open access",
            "elixirPlatform": [],
            "elixirNode": [
                "Germany"
            ],
            "elixirCommunity": [
                "Proteomics"
            ],
            "link": [
                {
                    "url": "https://github.com/medbioinf/pia",
                    "type": [
                        "Repository"
                    ],
                    "note": null
                }
            ],
            "download": [
                {
                    "url": "https://github.com/mpc-bioinformatics/pia",
                    "type": "Source code",
                    "note": null,
                    "version": null
                },
                {
                    "url": "http://bioconda.github.io/recipes/pia/README.html",
                    "type": "Software package",
                    "note": null,
                    "version": null
                },
                {
                    "url": "https://github.com/mpc-bioinformatics/pia/releases",
                    "type": "Binaries",
                    "note": null,
                    "version": null
                },
                {
                    "url": "https://hub.docker.com/r/julianusz/pia",
                    "type": "Container file",
                    "note": null,
                    "version": null
                }
            ],
            "documentation": [
                {
                    "url": "https://github.com/mpc-bioinformatics/pia/wiki",
                    "type": [
                        "General"
                    ],
                    "note": null
                }
            ],
            "publication": [
                {
                    "doi": "10.1021/acs.jproteome.5b00121",
                    "pmid": "25938255",
                    "pmcid": null,
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface",
                        "abstract": "Protein inference connects the peptide spectrum matches (PSMs) obtained from database search engines back to proteins, which are typically at the heart of most proteomics studies. Different search engines yield different PSMs and thus different protein lists. Analysis of results from one or multiple search engines is often hampered by different data exchange formats and lack of convenient and intuitive user interfaces. We present PIA, a flexible software suite for combining PSMs from different search engine runs and turning these into consistent results. PIA can be integrated into proteomics data analysis workflows in several ways. A user-friendly graphical user interface can be run either locally or (e.g., for larger core facilities) from a central server. For automated data processing, stand-alone tools are available. PIA implements several established protein inference algorithms and can combine results from different search engines seamlessly. On several benchmark data sets, we show that PIA can identify a larger number of proteins at the same protein FDR when compared to that using inference based on a single search engine. PIA supports the majority of established search engines and data in the mzIdentML standard format. It is implemented in Java and freely available at https://github.com/mpc-bioinformatics/pia.",
                        "date": "2015-07-02T00:00:00Z",
                        "citationCount": 53,
                        "authors": [
                            {
                                "name": "Uszkoreit J."
                            },
                            {
                                "name": "Maerkens A."
                            },
                            {
                                "name": "Perez-Riverol Y."
                            },
                            {
                                "name": "Meyer H.E."
                            },
                            {
                                "name": "Marcus K."
                            },
                            {
                                "name": "Stephan C."
                            },
                            {
                                "name": "Kohlbacher O."
                            },
                            {
                                "name": "Eisenacher M."
                            }
                        ],
                        "journal": "Journal of Proteome Research"
                    }
                },
                {
                    "doi": "10.1021/acs.jproteome.8b00723",
                    "pmid": "30474983",
                    "pmcid": null,
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Protein Inference Using PIA Workflows and PSI Standard File Formats",
                        "abstract": "Proteomics using LC-MS/MS has become one of the main methods to analyze the proteins in biological samples in high-throughput. But the existing mass-spectrometry instruments are still limited with respect to resolution and measurable mass ranges, which is one of the main reasons why shotgun proteomics is the major approach. Here proteins are digested, which leads to the identification and quantification of peptides instead. While often neglected, the important step of protein inference needs to be conducted to infer from the identified peptides to the actual proteins in the original sample. In this work, we highlight some of the previously published and newly added features of the tool PIA - Protein Inference Algorithms, which helps the user with the protein inference of measured samples. We also highlight the importance of the usage of PSI standard file formats, as PIA is the only current software supporting all available standards used for spectrum identification and protein inference. Additionally, we briefly describe the benefits of working with workflow environments for proteomics analyses and show the new features of the PIA nodes for the KNIME Analytics Platform. Finally, we benchmark PIA against a recently published data set for isoform detection. PIA is open source and available for download on GitHub (https://github.com/mpc-bioinformatics/pia) or directly via the community extensions inside the KNIME analytics platform.",
                        "date": "2019-02-01T00:00:00Z",
                        "citationCount": 25,
                        "authors": [
                            {
                                "name": "Uszkoreit J."
                            },
                            {
                                "name": "Perez-Riverol Y."
                            },
                            {
                                "name": "Eggers B."
                            },
                            {
                                "name": "Marcus K."
                            },
                            {
                                "name": "Eisenacher M."
                            }
                        ],
                        "journal": "Journal of Proteome Research"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Julian Uszkoreit",
                    "email": "julian.uszkoreit@rub.de",
                    "url": null,
                    "orcidid": "http://orcid.org/0000-0001-7522-4007",
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [
                        "Primary contact",
                        "Developer",
                        "Maintainer"
                    ],
                    "note": null
                },
                {
                    "name": "CUBiMed.RUB",
                    "email": "cubimed@rub.de",
                    "url": null,
                    "orcidid": null,
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