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{ "count": 7746, "next": "?page=2", "previous": null, "list": [ { "name": "IDIA", "description": "An integrative signal extractor for data-independent acquisition proteomics.", "homepage": "https://github.com/Biocomputing-Research-Group/IDIA", "biotoolsID": "idia", "biotoolsCURIE": "biotools:idia", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3646", "term": "Peptide database search" }, { "uri": "http://edamontology.org/operation_3767", "term": "Protein identification" }, { "uri": "http://edamontology.org/operation_3695", "term": "Filtering" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_3654", "term": "mzXML" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0943", "term": "Mass spectrum" }, "format": [ { "uri": "http://edamontology.org/format_3651", "term": "MGF" }, { "uri": "http://edamontology.org/format_3244", "term": "mzML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Java" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1109/BIBM55620.2022.9994873", "pmid": "37034305", "pmcid": "PMC10077956", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "IDIA: An Integrative Signal Extractor for Data-Independent Acquisition Proteomics", "abstract": "In proteomics, data-independent acquisition (DIA)has been shown to provide less biased and more reproducible results than data-dependent acquisition. Recently, many researchers have developed a series of methods to identify peptides and proteins by using spectrum libraries for DIA data. However, spectrum libraries are not always available for novel organisms or microbial communities. To detect peptides and proteins without a spectrum library, we developed IDIA, a library-free method using DIA data to generate pseudo-spectra that can be searched using conventional sequence database searching software. IDIA integrates two isotopic trace detection strategies and employs B-spline and Gaussian filters to help extract high-quality pseudo-spectra from the complex DIA data. The experimental results on human and yeast data demonstrated that our approach remarkably produced more peptide and protein identifications than the two state-of-the-art library-free methods, i.e., DIA-Umpire and Group-DIA. IDIA is freely available under the GNU GPL license at https://github.com/Biocomputing-Research-Group/IDIA.", "date": "2022-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Li J." }, { "name": "Pan C." }, { "name": "Guo X." } ], "journal": "Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022" } } ], "credit": [ { "name": "Xuan Guo", "email": "xuan.guo@unt.edu", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T20:53:22.903009Z", "lastUpdate": "2023-09-25T20:53:22.905395Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PROTHON", "description": "A local order parameter-based method for efficient comparison of protein ensembles.", "homepage": "https://github.com/PlotkinLab/Prothon", "biotoolsID": "prothon", "biotoolsCURIE": "biotools:prothon", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2997", "term": "Protein comparison" }, { "uri": "http://edamontology.org/operation_2476", "term": "Molecular dynamics" }, { "uri": "http://edamontology.org/operation_3891", "term": "Essential dynamics" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3870", "term": "Trajectory data" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_3872", "term": "Topology data" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0888", "term": "Structure similarity score" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0176", "term": "Molecular dynamics" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0078", "term": "Proteins" }, { "uri": "http://edamontology.org/topic_0593", "term": "NMR" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1021/acs.jcim.3c00145", "pmid": "37178169", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "PROTHON: A Local Order Parameter-Based Method for Efficient Comparison of Protein Ensembles", "abstract": "The comparison of protein conformational ensembles is of central importance in structural biology. However, there are few computational methods for ensemble comparison, and those that are readily available, such as ENCORE, utilize methods that are sufficiently computationally expensive to be prohibitive for large ensembles. Here, a new method is presented for efficient representation and comparison of protein conformational ensembles. The method is based on the representation of a protein ensemble as a vector of probability distribution functions (pdfs), with each pdf representing the distribution of a local structural property such as the number of contacts between Cβ atoms. Dissimilarity between two conformational ensembles is quantified by the Jensen-Shannon distance between the corresponding set of probability distribution functions. The method is validated for conformational ensembles generated by molecular dynamics simulations of ubiquitin, as well as experimentally derived conformational ensembles of a 130 amino acid truncated form of human tau protein. In the ubiquitin ensemble data set, the method was up to 88 times faster than the existing ENCORE software, while simultaneously utilizing 48 times fewer computing cores. We make the method available as a Python package, called PROTHON, and provide a GitHub page with the Python source code at https://github.com/PlotkinLab/Prothon.", "date": "2023-06-12T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Aina A." }, { "name": "Hsueh S.C.C." }, { "name": "Plotkin S.S." } ], "journal": "Journal of Chemical Information and Modeling" } } ], "credit": [ { "name": "Steven S. Plotkin", "email": "steve@phas.ubc.ca", "url": null, "orcidid": "https://orcid.org/0000-0001-8998-877X", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T19:18:38.412908Z", "lastUpdate": "2023-09-25T19:18:38.415458Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "high" }, { "name": "VT3D", "description": "Visualization toolbox for 3D transcriptomic data.", "homepage": "https://github.com/BGI-Qingdao/VT3D", "biotoolsID": "vt3d", "biotoolsCURIE": "biotools:vt3d", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" }, { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" }, { "uri": "http://edamontology.org/topic_3382", "term": "Imaging" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/BGI-Qingdao/VT3D_Browser", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [ { "url": "http://www.bgiocean.com/vt3d_example", "type": [ "Training material" ], "note": null } ], "publication": [ { "doi": "10.1016/J.JGG.2023.04.001", "pmid": "37054878", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "VT3D: a visualization toolbox for 3D transcriptomic data", "abstract": "Data visualization empowers researchers to communicate their results that support scientific reasoning in an intuitive way. 3D spatially resolved transcriptomic atlases constructed from multi-view and high-dimensional data have rapidly emerged as a powerful tool to unravel spatial gene expression patterns and cell type distribution in biological samples, revolutionizing the understanding of gene regulatory interactions and cell niches. However, limited accessible tools for data visualization impede the potential impact and application of this technology. Here we introduce VT3D, a visualization toolbox that allows users to explore 3D transcriptomic data, enabling gene expression projection to any 2D plane of interest, 2D virtual slice creation and visualization, and interactive 3D data browsing with surface model plots. In addition, it can either work on personal devices in standalone mode or be hosted as a web-based server. We apply VT3D to multiple datasets produced by the most popular techniques, including both sequencing-based approaches including Stereo-seq, spatial transcriptomics (ST), and Slide-seq, and imaging-based approaches including MERFISH and STARMap, and successfully build a 3D atlas database that allows interactive data browsing. We demonstrate that VT3D bridges the gap between researchers and spatially resolved transcriptomics, thus accelerating related studies such as embryogenesis and organogenesis processes. The source code of VT3D is available at https://github.com/BGI-Qingdao/VT3D, and the modeled atlas database is available at http://www.bgiocean.com/vt3d_example.", "date": "2023-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Guo L." }, { "name": "Li Y." }, { "name": "Qi Y." }, { "name": "Huang Z." }, { "name": "Han K." }, { "name": "Liu X." }, { "name": "Liu X." }, { "name": "Xu M." }, { "name": "Fan G." } ], "journal": "Journal of Genetics and Genomics" } } ], "credit": [ { "name": "Mengyang Xu", "email": "xumengyang@genomics.cn", "url": null, "orcidid": "https://orcid.org/0000-0002-4487-7088", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Guangyi Fan", "email": "fanguangyi@genomics.cn", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T18:46:03.722676Z", "lastUpdate": "2023-09-25T18:46:03.725417Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "high" }, { "name": "mBONITA", "description": "Multi-omics boolean omics network invariant-time analysis.", "homepage": "https://github.com/Thakar-Lab/mBONITA", "biotoolsID": "mbonita", "biotoolsCURIE": "biotools:mbonita", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3928", "term": "Pathway analysis" }, { "uri": "http://edamontology.org/operation_3927", "term": "Network analysis" }, { "uri": "http://edamontology.org/operation_3501", "term": "Enrichment analysis" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_3308", "term": "Transcriptomics" }, { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "C", "Python" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1021/ACS.JPROTEOME.2C00730", "pmid": "37000949", "pmcid": "PMC10167691", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Executable Network Models of Integrated Multiomics Data", "abstract": "Multiomics profiling provides a holistic picture of a condition being examined and captures the complexity of signaling events, beginning from the original cause (environmental or genetic), to downstream functional changes at multiple molecular layers. Pathway enrichment analysis has been used with multiomics data sets to characterize signaling mechanisms. However, technical and biological variability between these layered data limit an integrative computational analyses. We present a Boolean network-based method, multiomics Boolean Omics Network Invariant-Time Analysis (mBONITA), to integrate omics data sets that quantify multiple molecular layers. mBONITA utilizes prior knowledge networks to perform topology-based pathway analysis. In addition, mBONITA identifies genes that are consistently modulated across molecular measurements by combining observed fold-changes and variance, with a measure of node (i.e., gene or protein) influence over signaling, and a measure of the strength of evidence for that gene across data sets. We used mBONITA to integrate multiomics data sets from RAMOS B cells treated with the immunosuppressant drug cyclosporine A under varying O2 tensions to identify pathways involved in hypoxia-mediated chemotaxis. We compare mBONITA’s performance with 6 other pathway analysis methods designed for multiomics data and show that mBONITA identifies a set of pathways with evidence of modulation across all omics layers. mBONITA is freely available at https://github.com/Thakar-Lab/mBONITA.", "date": "2023-05-05T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Palshikar M.G." }, { "name": "Min X." }, { "name": "Crystal A." }, { "name": "Meng J." }, { "name": "Hilchey S.P." }, { "name": "Zand M.S." }, { "name": "Thakar J." } ], "journal": "Journal of Proteome Research" } } ], "credit": [ { "name": "Juilee Thakar", "email": "Juilee_Thakar@URMC.rochester.edu", "url": null, "orcidid": "https://orcid.org/0000-0003-4479-4183", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T18:35:03.752451Z", "lastUpdate": "2023-09-25T18:35:03.755242Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "dipwmsearch", "description": "Python package for searching di-PWM motifs.", "homepage": "https://gite.lirmm.fr/rivals/dipwmsearch/", "biotoolsID": "dipwmsearch", "biotoolsCURIE": "biotools:dipwmsearch", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0239", "term": "Sequence motif recognition" }, { "uri": "http://edamontology.org/operation_2421", "term": "Database search" }, { "uri": "http://edamontology.org/operation_0445", "term": "Transcription factor binding site prediction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0160", "term": "Sequence sites, features and motifs" }, { "uri": "http://edamontology.org/topic_3673", "term": "Whole genome sequencing" }, { "uri": "http://edamontology.org/topic_3169", "term": "ChIP-seq" }, { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_3295", "term": "Epigenetics" } ], "operatingSystem": [ "Linux", "Mac" ], "language": [ "Python" ], "license": "CECILL-B", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://pypi.org/project/dipwmsearch/", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/BIOINFORMATICS/BTAD141", "pmid": "37010504", "pmcid": "PMC10081870", "type": [], "version": null, "note": null, "metadata": { "title": "dipwmsearch: a Python package for searching di-PWM motifs", "abstract": "Motivation: Seeking probabilistic motifs in a sequence is a common task to annotate putative transcription factor binding sites or other RNA/DNA binding sites. Useful motif representations include position weight matrices (PWMs), dinucleotide PWMs (di-PWMs), and hidden Markov models (HMMs). Dinucleotide PWMs not only combine the simplicity of PWMs—a matrix form and a cumulative scoring function—but also incorporate dependency between adjacent positions in the motif (unlike PWMs which disregard any dependency). For instance to represent binding sites, the HOCOMOCO database provides di-PWM motifs derived from experimental data. Currently, two programs, SPRy-SARUS and MOODS, can search for occurrences of di-PWMs in sequences. Results: We propose a Python package called dipwmsearch, which provides an original and efficient algorithm for this task (it first enumerates matching words for the di-PWM, and then searches these all at once in the sequence, even if the latter contains IUPAC codes). The user benefits from an easy installation via Pypi or conda, a comprehensive documentation, and executable scripts that facilitate the use of di-PWMs.", "date": "2023-04-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Mille M." }, { "name": "Ripoll J." }, { "name": "Cazaux B." }, { "name": "Rivals E." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Eric Rivals", "email": "rivals@lirmm.fr", "url": null, "orcidid": "https://orcid.org/0000-0003-3791-3973", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T18:20:46.182047Z", "lastUpdate": "2023-09-25T18:20:46.184376Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "DeepSTABp", "description": "An AI based web tool to predict the melting temperature (Tm) of proteins based on their amino acid sequence and various growth conditions.", "homepage": "https://csb-deepstabp.bio.rptu.de", "biotoolsID": "deepstabp", "biotoolsCURIE": "biotools:deepstabp", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3096", "term": "Editing" }, { "uri": "http://edamontology.org/operation_0331", "term": "Variant effect prediction" }, { "uri": "http://edamontology.org/operation_3092", "term": "Protein feature detection" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" }, { "uri": "http://edamontology.org/format_1964", "term": "plain text format (unformatted)" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0897", "term": "Protein property" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Desktop application" ], "topic": [ { "uri": "http://edamontology.org/topic_0130", "term": "Protein folding, stability and design" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0080", "term": "Sequence analysis" }, { "uri": "http://edamontology.org/topic_0601", "term": "Protein modifications" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python", "JavaScript" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/CSBiology/deepStabP", "type": [ "Repository" ], "note": null }, { "url": "https://git.nfdi4plants.org/f_jung/deepstabp", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.3390/IJMS24087444", "pmid": "37108605", "pmcid": "PMC10138888", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "DeepSTABp: A Deep Learning Approach for the Prediction of Thermal Protein Stability", "abstract": "Proteins are essential macromolecules that carry out a plethora of biological functions. The thermal stability of proteins is an important property that affects their function and determines their suitability for various applications. However, current experimental approaches, primarily thermal proteome profiling, are expensive, labor-intensive, and have limited proteome and species coverage. To close the gap between available experimental data and sequence information, a novel protein thermal stability predictor called DeepSTABp has been developed. DeepSTABp uses a transformer-based protein language model for sequence embedding and state-of-the-art feature extraction in combination with other deep learning techniques for end-to-end protein melting temperature prediction. DeepSTABp can predict the thermal stability of a wide range of proteins, making it a powerful and efficient tool for large-scale prediction. The model captures the structural and biological properties that impact protein stability, and it allows for the identification of the structural features that contribute to protein stability. DeepSTABp is available to the public via a user-friendly web interface, making it accessible to researchers in various fields.", "date": "2023-04-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Jung F." }, { "name": "Frey K." }, { "name": "Zimmer D." }, { "name": "Muhlhaus T." } ], "journal": "International Journal of Molecular Sciences" } } ], "credit": [ { "name": "Timo Mühlhaus", "email": "timo.muehlhaus@rptu.de", "url": null, "orcidid": "https://orcid.org/0000-0003-3925-6778", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T17:54:30.731190Z", "lastUpdate": "2023-09-25T17:54:30.733846Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "iSnoDi-MDRF", "description": "Identifying snoRNA-disease associations based on multiple biological data by ranking framework.", "homepage": "http://bliulab.net/iSnoDi-MDRF/", "biotoolsID": "isnodi_mdrf", "biotoolsCURIE": "biotools:isnodi_mdrf", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_2478", "term": "Nucleic acid sequence analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3495", "term": "RNA sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1772", "term": "Score" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_0634", "term": "Pathology" }, { "uri": "http://edamontology.org/topic_3361", "term": "Laboratory techniques" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1109/TCBB.2023.3258448", "pmid": "37030816", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "iSnoDi-MDRF: identifying snoRNA-disease associations based on multiple biological data by ranking framework", "abstract": "Accumulating evidence indicates that the dysregulation of small nucleolar RNAs (snoRNAs) is relevant with diseases. Identifying snoRNA-disease associations by computational methods is desired for biologists, which can save considerable costs and time compared biological experiments. However, it still faces some challenges as followings: (i) Many snoRNAs are detected in recent years, but only a few snoRNAs have been proved to be associated with diseases; (ii) Computational predictors trained with only a few known snoRNA-disease associations fail to accurately identify the snoRNA-disease associations. In this study, we propose a ranking framework, called iSnoDi-MDRF, to identify potential snoRNA-disease associations based on multiple biological data, which has the following highlights: (i) iSnoDi-MDRF integrates ranking framework, which is not only able to identify potential associations between known snoRNAs and diseases, but also can identify diseases associated with new snoRNAs. (ii) Known gene-disease associations are employed to help train a mature model for predicting snoRNA-disease association. Experimental results illustrate that iSnoDi-MDRF is very suitable for identifying potential snoRNA-disease associations. The web server of iSnoDi-MDRF predictor is freely available at <uri>http://bliulab.net/iSnoDi-MDRF/</uri>.", "date": "2023-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Zhang W." }, { "name": "Liu B." } ], "journal": "IEEE/ACM Transactions on Computational Biology and Bioinformatics" } } ], "credit": [ { "name": "Bin Liu", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0003-3685-9469", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T17:45:48.313559Z", "lastUpdate": "2023-09-25T17:45:48.316096Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PredinID", "description": "Predicting pathogenic inframe indels in humans through graph convolution neural network with graph sampling technique.", "homepage": "http://predinid.bio.aielab.cc/", "biotoolsID": "predinid", "biotoolsCURIE": "biotools:predinid", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3461", "term": "Virulence prediction" }, { "uri": "http://edamontology.org/operation_3927", "term": "Network analysis" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3498", "term": "Sequence variations" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1772", "term": "Score" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_0634", "term": "Pathology" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_3810", "term": "Agricultural science" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "http://predinid.bio.aielab.cc/static/userDownload/PredinID.rar", "type": "Software package", "note": null, "version": null } ], "documentation": [], "publication": [ { "doi": "10.1109/TCBB.2023.3266232", "pmid": "37040252", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "PredinID: predicting pathogenic inframe indels in human through graph convolution neural network with graph sampling technique", "abstract": "Inframe insertion/deletion (indel) variants may alter protein sequence and function, which are closely related to an extensive variety of diseases. Although recent researches have paid attention to the associations between inframe indels and diseases, modeling indels in silico and interpreting their pathogenicity remain challenging, mainly due to the lack of experimental information and computational methodologies. In this paper, we propose a novel computational method named PredinID (Predictor for inframe InDels) via graph convolutional network (GCN). PredinID leverages k-nearest neighbor algorithm to construct the feature graph for aggregating more informative representation, regarding the pathogenic inframe indel prediction as a node classification task. An edge-based sampling strategy is designed for extracting information from both the potential connections of feature space and the topological structure of subgraphs. Evaluated by 5-fold cross-validations, the PredinID method achieves satisfactory performance and is superior to four classic machine learning algorithms and two GCN methods. Comprehensive experiments show that PredinID has superior performances when compared with the state-of-the-art methods on the independent test set. Moreover, we also implement a web server at http://predinid.bio.aielab.cc/, to facilitate the use of the model.", "date": "2023-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Yue Z." }, { "name": "Xiang Y." }, { "name": "Chen G." }, { "name": "Wang X." }, { "name": "Li K." }, { "name": "Zhang Y." } ], "journal": "IEEE/ACM Transactions on Computational Biology and Bioinformatics" } } ], "credit": [ { "name": "Zhenyu Yue", "email": "zhenyuyue@ahau.edu.cn", "url": null, "orcidid": "https://orcid.org/0000-0002-9370-2540", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Ke Li", "email": null, "url": null, "orcidid": "https://orcid.org/0000-0001-7279-5015", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T17:27:23.425935Z", "lastUpdate": "2023-09-25T17:27:23.428576Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PXStools", "description": "R package of tools for conducting exposure-wide analysis and deriving polyexposure risk scores.", "homepage": "https://github.com/yixuanh/PXStools", "biotoolsID": "pxstools", "biotoolsCURIE": "biotools:pxstools", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3659", "term": "Regression analysis" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" }, { "uri": "http://edamontology.org/operation_3435", "term": "Standardisation and normalisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_3517", "term": "GWAS study" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/IJE/DYAC216", "pmid": null, "pmcid": "PMC10114106", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Software Application Profile: PXStools—an R package of tools for conducting exposure-wide analysis and deriving polyexposure risk scores", "abstract": "Motivation: Investigating the aggregate burden of environmental factors on human traits and diseases requires consideration of the entire ‘exposome’. However, current studies primarily focus on a single exposure or a handful of exposures at a time, without considering how multiple exposures may be simultaneously associated with each other or with the phenotype. Polyexposure risk scores (PXS) have been shown to predict and stratify risk for disease beyond or complementary to genetic and clinical risk. PXStools provides an analytical package to standardize exposome-wide studies as well as derive and validate polyexposure risk scores. Implementation: PXStools is a package for the statistical R. General features: The package allows users to (i) conduct exposure-wide association studies; (ii) derive and validate polyexposure risk scores with and without accounting for exposure interactions, using new approaches in regression modelling (hierarchical lasso);(iii) compare goodness of fit between models with and without multiple exposures; and (iv) visualize results. A data frame with a unique identifier, phenotype and exposures is needed as the only input. Various customizations are allowed including data preprocessing (removing missing or unwanted responses), covariates adjustment, multiple hypothesis correction and model specification (linear, logistic, survival).", "date": "2023-04-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "He Y." }, { "name": "Patel C.J." } ], "journal": "International Journal of Epidemiology" } } ], "credit": [ { "name": "Chirag J Patel", "email": "chirag_patel@hms.harvard.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-8756-8525", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T17:15:56.465153Z", "lastUpdate": "2023-09-25T17:15:56.467728Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "GRaNPA", "description": "R package for assessing the biological relevance of any TF-Gene GRNs using a machine learning framework to predict cell-type specific differential expression.", "homepage": "https://git.embl.de/grp-zaugg/GRaNPA", "biotoolsID": "granpa", "biotoolsCURIE": "biotools:granpa", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_1781", "term": "Gene regulatory network analysis" }, { "uri": "http://edamontology.org/operation_2437", "term": "Gene regulatory network prediction" }, { "uri": "http://edamontology.org/operation_3928", "term": "Pathway analysis" }, { "uri": "http://edamontology.org/operation_3891", "term": "Essential dynamics" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" }, { "uri": "http://edamontology.org/topic_0749", "term": "Transcription factors and regulatory sites" }, { "uri": "http://edamontology.org/topic_3295", "term": "Epigenetics" }, { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_0204", "term": "Gene regulation" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R" ], "license": "Artistic-2.0", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://grp-zaugg.embl-community.io/GRaNPA", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.15252/MSB.202311627", "pmid": "37073532", "pmcid": "PMC10258561", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "GRaNIE and GRaNPA: inference and evaluation of enhancer-mediated gene regulatory networks", "abstract": "Enhancers play a vital role in gene regulation and are critical in mediating the impact of noncoding genetic variants associated with complex traits. Enhancer activity is a cell-type-specific process regulated by transcription factors (TFs), epigenetic mechanisms and genetic variants. Despite the strong mechanistic link between TFs and enhancers, we currently lack a framework for jointly analysing them in cell-type-specific gene regulatory networks (GRN). Equally important, we lack an unbiased way of assessing the biological significance of inferred GRNs since no complete ground truth exists. To address these gaps, we present GRaNIE (Gene Regulatory Network Inference including Enhancers) and GRaNPA (Gene Regulatory Network Performance Analysis). GRaNIE (https://git.embl.de/grp-zaugg/GR aNIE) builds enhancer-mediated GRNs based on covariation of chromatin accessibility and RNA-seq across samples (e.g. individuals), while GRaNPA (https://git.embl.de/grp-zaugg/GRaNPA) assesses the performance of GRNs for predicting cell-type-specific differential expression. We demonstrate their power by investigating gene regulatory mechanisms underlying the response of macrophages to infection, cancer and common genetic traits including autoimmune diseases. Finally, our methods identify the TF PURA as a putative regulator of pro-inflammatory macrophage polarisation.", "date": "2023-06-12T00:00:00Z", "citationCount": 3, "authors": [ { "name": "Kamal A." }, { "name": "Arnold C." }, { "name": "Claringbould A." }, { "name": "Moussa R." }, { "name": "Servaas N.H." }, { "name": "Kholmatov M." }, { "name": "Daga N." }, { "name": "Nogina D." }, { "name": "Mueller-Dott S." }, { "name": "Reyes-Palomares A." }, { "name": "Palla G." }, { "name": "Sigalova O." }, { "name": "Bunina D." }, { "name": "Pabst C." }, { "name": "Zaugg J.B." } ], "journal": "Molecular Systems Biology" } } ], "credit": [ { "name": "Judith B Zaugg", "email": "judith.zaugg@embl.de", "url": null, "orcidid": "https://orcid.org/0000-0001-8324-4040", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2023-09-25T17:04:35.235693Z", "lastUpdate": "2023-09-25T17:04:35.238281Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "high" } ] }