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{ "count": 29877, "next": "?page=2", "previous": null, "list": [ { "name": "CircSI-SSL", "description": "circRNA-binding site identification based on self-supervised learning.", "homepage": "https://github.com/cc646201081/CircSI-SSL", "biotoolsID": "circsi-ssl", "biotoolsCURIE": "biotools:circsi-ssl", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2575", "term": "Binding site prediction" }, { "uri": "http://edamontology.org/operation_3937", "term": "Feature extraction" }, { "uri": "http://edamontology.org/operation_3436", "term": "Aggregation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_0099", "term": "RNA" }, { "uri": "http://edamontology.org/topic_3794", "term": "RNA immunoprecipitation" } ], "operatingSystem": [], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/bioinformatics/btae004", "pmid": "38180876", "pmcid": "PMC10789309", "type": [], "version": null, "note": null, "metadata": { "title": "CircSI-SSL: CircRNA-binding site identification based on self-supervised learning", "abstract": "Motivation: In recent years, circular RNAs (circRNAs), the particular form of RNA with a closed-loop structure, have attracted widespread attention due to their physiological significance (they can directly bind proteins), leading to the development of numerous protein site identification algorithms. Unfortunately, these studies are supervised and require the vast majority of labeled samples in training to produce superior performance. But the acquisition of sample labels requires a large number of biological experiments and is difficult to obtain. Results: To resolve this matter that a great deal of tags need to be trained in the circRNA-binding site prediction task, a self-supervised learning binding site identification algorithm named CircSI-SSL is proposed in this article. According to the survey, this is unprecedented in the research field. Specifically, CircSI-SSL initially combines multiple feature coding schemes and employs RNA_Transformer for cross-view sequence prediction (self-supervised task) to learn mutual information from the multi-view data, and then fine-tuning with only a few sample labels. Comprehensive experiments on six widely used circRNA datasets indicate that our CircSI-SSL algorithm achieves excellent performance in comparison to previous algorithms, even in the extreme case where the ratio of training data to test data is 1:9. In addition, the transplantation experiment of six linRNA datasets without network modification and hyperparameter adjustment shows that CircSI-SSL has good scalability. In summary, the prediction algorithm based on self-supervised learning proposed in this article is expected to replace previous supervised algorithms and has more extensive application value.", "date": "2024-01-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Cao C." }, { "name": "Wang C." }, { "name": "Yang S." }, { "name": "Zou Q." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Quan Zou", "email": "zouquan@nclab.net", "url": null, "orcidid": "https://orcid.org/0000-0001-6406-1142", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Chao Cao", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-05-18T15:25:26.545304Z", "lastUpdate": "2024-05-18T15:25:26.547617Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "SeedMatchR", "description": "The goal of SeedMatchR is to help users identify potential seed-mediated effects in their RNAseq data.", "homepage": "https://github.com/tacazares/SeedMatchR", "biotoolsID": "seedmatchr", "biotoolsCURIE": "biotools:seedmatchr", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3223", "term": "Differential gene expression profiling" }, { "uri": "http://edamontology.org/operation_3792", "term": "miRNA expression analysis" }, { "uri": "http://edamontology.org/operation_0465", "term": "siRNA binding specificity prediction" }, { "uri": "http://edamontology.org/operation_0463", "term": "miRNA target prediction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_0659", "term": "Functional, regulatory and non-coding RNA" }, { "uri": "http://edamontology.org/topic_3512", "term": "Gene transcripts" }, { "uri": "http://edamontology.org/topic_3170", "term": "RNA-Seq" }, { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_0108", "term": "Protein expression" } ], "operatingSystem": [ "Mac", "Windows" ], "language": [ "R" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/bioinformatics/btae011", "pmid": "38192001", "pmcid": "PMC10799297", "type": [], "version": null, "note": null, "metadata": { "title": "SeedMatchR: identify off-target effects mediated by siRNA seed regions in RNA-seq experiments", "abstract": "Motivation: On-target gene knockdown, using siRNA, ideally results from binding fully complementary regions in mRNA transcripts to induce direct cleavage. Off-target siRNA gene knockdown can occur through several modes, one being a seed-mediated mechanism mimicking miRNA gene regulation. Seed-mediated off-target effects occur when the ∼8 nucleotides at the 5' end of the guide strand, called a seed region, bind the 3' untranslated regions of mRNA, causing reduced translation. Experiments using siRNA knockdown paired with RNA-seq can be used to detect siRNA sequences with off-target effects driven by the seed region. However, there are limited computational tools designed specifically for detecting siRNA off-target effects mediated by the seed region in differential gene expression experiments. Results: SeedMatchR is an R package developed to provide users a single, unified resource for detecting and visualizing seed-mediated off-target effects of siRNA using RNA-seq experiments. SeedMatchR is designed to extend current differential expression analysis tools, such as DESeq2, by annotating results with predicted seed matches. Using publicly available data, we demonstrate the ability of SeedMatchR to detect cumulative changes in differential gene expression attributed to siRNA seed region activity. Availability: SeedMatchR is available on CRAN. Documentation and example workflows are available through the SeedMatchR GitHub page at https://github.com/tacazares/SeedMatchR.", "date": "2024-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Cazares T." }, { "name": "Higgs R.E." }, { "name": "Wang J." }, { "name": "Ozer H.G." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Tareian Cazares", "email": "tareian.cazares@lilly.com", "url": null, "orcidid": "https://orcid.org/0000-0003-4624-6156", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Hatice Gulcin Ozer", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-05-18T15:23:08.553789Z", "lastUpdate": "2024-05-18T15:23:08.555952Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "DisoFLAG", "description": "Prediction of protein intrinsic disorder and its functions using graph-based interaction protein language model.", "homepage": "https://github.com/YihePang/DisoFLAG", "biotoolsID": "disoflag", "biotoolsCURIE": "biotools:disoflag", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3904", "term": "Protein disorder prediction" }, { "uri": "http://edamontology.org/operation_0470", "term": "Protein secondary structure prediction (coils)" }, { "uri": "http://edamontology.org/operation_2492", "term": "Protein interaction prediction" }, { "uri": "http://edamontology.org/operation_3901", "term": "RNA-binding protein prediction" }, { "uri": "http://edamontology.org/operation_3900", "term": "DNA-binding protein prediction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3300", "term": "Physiology" }, { "uri": "http://edamontology.org/topic_3538", "term": "Protein disordered structure" }, { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0593", "term": "NMR" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1186/s12915-023-01803-y", "pmid": "38166858", "pmcid": "PMC10762911", "type": [], "version": null, "note": null, "metadata": { "title": "DisoFLAG: accurate prediction of protein intrinsic disorder and its functions using graph-based interaction protein language model", "abstract": "Intrinsically disordered proteins and regions (IDPs/IDRs) are functionally important proteins and regions that exist as highly dynamic conformations under natural physiological conditions. IDPs/IDRs exhibit a broad range of molecular functions, and their functions involve binding interactions with partners and remaining native structural flexibility. The rapid increase in the number of proteins in sequence databases and the diversity of disordered functions challenge existing computational methods for predicting protein intrinsic disorder and disordered functions. A disordered region interacts with different partners to perform multiple functions, and these disordered functions exhibit different dependencies and correlations. In this study, we introduce DisoFLAG, a computational method that leverages a graph-based interaction protein language model (GiPLM) for jointly predicting disorder and its multiple potential functions. GiPLM integrates protein semantic information based on pre-trained protein language models into graph-based interaction units to enhance the correlation of the semantic representation of multiple disordered functions. The DisoFLAG predictor takes amino acid sequences as the only inputs and provides predictions of intrinsic disorder and six disordered functions for proteins, including protein-binding, DNA-binding, RNA-binding, ion-binding, lipid-binding, and flexible linker. We evaluated the predictive performance of DisoFLAG following the Critical Assessment of protein Intrinsic Disorder (CAID) experiments, and the results demonstrated that DisoFLAG offers accurate and comprehensive predictions of disordered functions, extending the current coverage of computationally predicted disordered function categories. The standalone package and web server of DisoFLAG have been established to provide accurate prediction tools for intrinsic disorders and their associated functions.", "date": "2024-12-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Pang Y." }, { "name": "Liu B." } ], "journal": "BMC Biology" } } ], "credit": [ { "name": "Bin Liu", "email": "bliu@bliulab.net", "url": null, "orcidid": "https://orcid.org/0000-0001-7338-5739", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Yihe Pang", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-05-18T15:19:43.372407Z", "lastUpdate": "2024-05-18T15:19:43.374652Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "PLANNER", "description": "Multi-scale deep language model for the origins of replication site prediction.", "homepage": "http://planner.unimelb-biotools.cloud.edu.au/", "biotoolsID": "planner", "biotoolsCURIE": "biotools:planner", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" } ], "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/jbhi.2024.3349584", "pmid": "38190667", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "PLANNER: A Multi-Scale Deep Language Model for the Origins of Replication Site Prediction", "abstract": "Origins of replication sites (ORIs) are crucial genomic regions where DNA replication initiation takes place, playing pivotal roles in fundamental biological processes like cell division, gene expression regulation, and DNA integrity. Accurate identification of ORIs is essential for comprehending cell replication, gene expression, and mutation-related diseases. However, experimental approaches for ORI identification are often expensive and time-consuming, leading to the growing popularity of computational methods. In this study, we present PLANNER (DeeP LeArNiNg prEdictor for ORI), a novel approach for species-specific and cell-specific prediction of eukaryotic ORIs. PLANNER uses the multi-scale k-tuple sequences as input and employs the DNABERT pre-training model with transfer learning and ensemble learning strategies to train accurate predictive models. Extensive empirical test results demonstrate that PLANNER achieved superior predictive performance compared to state-of-the-art approaches, including iOri-Euk, Stack-ORI, and ORI-Deep, within specific cell types and across different cell types. Furthermore, by incorporating an interpretable analysis mechanism, we provide insights into the learned patterns, facilitating the mapping from discovering important sequential determinants to comprehensively analysing their biological functions.", "date": "2024-04-01T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Wang C." }, { "name": "He Z." }, { "name": "Jia R." }, { "name": "Pan S." }, { "name": "Coin L.J.M." }, { "name": "Song J." }, { "name": "Li F." } ], "journal": "IEEE Journal of Biomedical and Health Informatics" } } ], "credit": [ { "name": "Cong Wang", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-05-18T15:05:00.968261Z", "lastUpdate": "2024-05-18T15:05:00.970796Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "CLOUDe", "description": "CLOUDe is a suite of machine learning methods for predicting evolutionary targets of gene deletion events from expression data.", "homepage": "https://github.com/anddssan/CLOUDe", "biotoolsID": "cloude", "biotoolsCURIE": "biotools:cloude", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0314", "term": "Gene expression profiling" }, { "uri": "http://edamontology.org/operation_2436", "term": "Gene-set enrichment analysis" }, { "uri": "http://edamontology.org/operation_0553", "term": "Gene tree construction" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_3299", "term": "Evolutionary biology" }, { "uri": "http://edamontology.org/topic_0203", "term": "Gene expression" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" } ], "operatingSystem": [], "language": [ "R" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/bioadv/vbae002", "pmid": "38282974", "pmcid": "PMC10812876", "type": [], "version": null, "note": null, "metadata": { "title": "Predicting evolutionary targets and parameters of gene deletion from expression data", "abstract": "Motivation: Gene deletion is traditionally thought of as a nonadaptive process that removes functional redundancy from genomes, such that it generally receives less attention than duplication in evolutionary turnover studies. Yet, mounting evidence suggests that deletion may promote adaptation via the “less-is-more” evolutionary hypothesis, as it often targets genes harboring unique sequences, expression profiles, and molecular functions. Hence, predicting the relative prevalence of redundant and unique functions among genes targeted by deletion, as well as the parameters underlying their evolution, can shed light on the role of gene deletion in adaptation. Results: Here, we present CLOUDe, a suite of machine learning methods for predicting evolutionary targets of gene deletion events from expression data. Specifically, CLOUDe models expression evolution as an Ornstein–Uhlenbeck process, and uses multi-layer neural network, extreme gradient boosting, random forest, and support vector machine architectures to predict whether deleted genes are “redundant” or “unique”, as well as several parameters underlying their evolution. We show that CLOUDe boasts high power and accuracy in differentiating between classes, and high accuracy and precision in estimating evolutionary parameters, with optimal performance achieved by its neural network architecture. Application of CLOUDe to empirical data from Drosophila suggests that deletion primarily targets genes with unique functions, with further analysis showing these functions to be enriched for protein deubiquitination. Thus, CLOUDe represents a key advance in learning about the role of gene deletion in functional evolution and adaptation.", "date": "2024-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "dos Santos A.L.C." }, { "name": "DeGiorgio M." }, { "name": "Assis R." } ], "journal": "Bioinformatics Advances" } } ], "credit": [ { "name": "Andre Luiz Campelo dos Santos", "email": "acampelodossanto@fau.edu", "url": null, "orcidid": "https://orcid.org/0000-0002-5577-1967", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-05-18T15:03:19.968392Z", "lastUpdate": "2024-05-18T15:03:19.970577Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "EvORanker", "description": "EvORanker is an interactive web tool for prioritizing candidate genes using coevolution and STRING.", "homepage": "https://ccanavati.shinyapps.io/EvORanker/", "biotoolsID": "evoranker", "biotoolsCURIE": "biotools:evoranker", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3226", "term": "Variant prioritisation" }, { "uri": "http://edamontology.org/operation_3227", "term": "Variant calling" }, { "uri": "http://edamontology.org/operation_2422", "term": "Data retrieval" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0622", "term": "Genomics" }, { "uri": "http://edamontology.org/topic_3676", "term": "Exome sequencing" }, { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_3293", "term": "Phylogenetics" } ], "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": "10.1186/s13073-023-01276-2", "pmid": "38178268", "pmcid": "PMC10765705", "type": [], "version": null, "note": null, "metadata": { "title": "Using multi-scale genomics to associate poorly annotated genes with rare diseases", "abstract": "Background: Next-generation sequencing (NGS) has significantly transformed the landscape of identifying disease-causing genes associated with genetic disorders. However, a substantial portion of sequenced patients remains undiagnosed. This may be attributed not only to the challenges posed by harder-to-detect variants, such as non-coding and structural variations but also to the existence of variants in genes not previously associated with the patient’s clinical phenotype. This study introduces EvORanker, an algorithm that integrates unbiased data from 1,028 eukaryotic genomes to link mutated genes to clinical phenotypes. Methods: EvORanker utilizes clinical data, multi-scale phylogenetic profiling, and other omics data to prioritize disease-associated genes. It was evaluated on solved exomes and simulated genomes, compared with existing methods, and applied to 6260 knockout genes with mouse phenotypes lacking human associations. Additionally, EvORanker was made accessible as a user-friendly web tool. Results: In the analyzed exomic cohort, EvORanker accurately identified the “true” disease gene as the top candidate in 69% of cases and within the top 5 candidates in 95% of cases, consistent with results from the simulated dataset. Notably, EvORanker outperformed existing methods, particularly for poorly annotated genes. In the case of the 6260 knockout genes with mouse phenotypes, EvORanker linked 41% of these genes to observed human disease phenotypes. Furthermore, in two unsolved cases, EvORanker successfully identified DLGAP2 and LPCAT3 as disease candidates for previously uncharacterized genetic syndromes. Conclusions: We highlight clade-based phylogenetic profiling as a powerful systematic approach for prioritizing potential disease genes. Our study showcases the efficacy of EvORanker in associating poorly annotated genes to disease phenotypes observed in patients. The EvORanker server is freely available at https://ccanavati.shinyapps.io/EvORanker/ .", "date": "2024-12-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Canavati C." }, { "name": "Sherill-Rofe D." }, { "name": "Kamal L." }, { "name": "Bloch I." }, { "name": "Zahdeh F." }, { "name": "Sharon E." }, { "name": "Terespolsky B." }, { "name": "Allan I.A." }, { "name": "Rabie G." }, { "name": "Kawas M." }, { "name": "Kassem H." }, { "name": "Avraham K.B." }, { "name": "Renbaum P." }, { "name": "Levy-Lahad E." }, { "name": "Kanaan M." }, { "name": "Tabach Y." } ], "journal": "Genome Medicine" } } ], "credit": [ { "name": "Yuval Tabach", "email": "yuval.tabach@mail.huji.ac.il", "url": null, "orcidid": "https://orcid.org/0000-0001-9521-3217", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Christina Canavati", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-05-18T14:51:38.985638Z", "lastUpdate": "2024-05-18T14:51:38.988011Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "DIAgui", "description": "Shiny application and R package to process the output from DIA-NN.\nIt returns the quantification of either the precursors, the peptides, the proteins, or the genes thanks to the MaxLFQ algorithm. In addition, the latest version provides the Top3 and iBAQ quantification and the number of peptides used for the quantification. In the end, DIAgui produces ready-to-interpret files from the results of DIA mass spectrometry analysis and provides visualization and statistical tools that can be used in a user-friendly way.", "homepage": "https://github.com/marseille-proteomique/DIAgui", "biotoolsID": "diagui", "biotoolsCURIE": "biotools:diagui", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3799", "term": "Quantification" }, { "uri": "http://edamontology.org/operation_2409", "term": "Data handling" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application", "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3520", "term": "Proteomics experiment" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "R", "C++" ], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/bioadv/vbae001", "pmid": "38249340", "pmcid": "PMC10799745", "type": [], "version": null, "note": null, "metadata": { "title": "DIAgui: a Shiny application to process the output from DIA-NN", "abstract": "DIAgui is an R package to simplify the processing of the report file from the DIA-NN software thanks to a Shiny application. It returns the quantification of either the precursors, the peptides, the proteins, or the genes thanks to the MaxLFQ algorithm. In addition, the latest version provides the Top3 and iBAQ quantification and the number of peptides used for the quantification. In the end, DIAgui produces ready-to-interpret files from the results of DIA mass spectrometry analysis and provides visualization and statistical tools that can be used in a user-friendly way.", "date": "2024-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Gerault M.-A." }, { "name": "Camoin L." }, { "name": "Granjeaud S." } ], "journal": "Bioinformatics Advances" } } ], "credit": [ { "name": "Marc-Antoine Gerault", "email": "marc-antoine.gerault@inserm.fr", "url": null, "orcidid": "https://orcid.org/0009-0000-7430-3467", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Luc Camoin", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Samuel Granjeaud", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-05-18T14:49:23.007488Z", "lastUpdate": "2024-05-18T14:49:23.009468Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "CircNetVis", "description": "Interactive web application for visualizing interaction networks of circular RNAs.", "homepage": "https://www.meb.ki.se/shiny/truvu/CircNetVis/", "biotoolsID": "circnetvis", "biotoolsCURIE": "biotools:circnetvis", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3925", "term": "Network visualisation" }, { "uri": "http://edamontology.org/operation_3094", "term": "Protein interaction network prediction" }, { "uri": "http://edamontology.org/operation_0276", "term": "Protein interaction network analysis" }, { "uri": "http://edamontology.org/operation_0335", "term": "Formatting" } ], "input": [], "output": [], "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_3512", "term": "Gene transcripts" }, { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_3794", "term": "RNA immunoprecipitation" } ], "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": "10.1186/s12859-024-05646-4", "pmid": "38233808", "pmcid": "PMC10795305", "type": [], "version": null, "note": null, "metadata": { "title": "CircNetVis: an interactive web application for visualizing interaction networks of circular RNAs", "abstract": "Analyzing the interactions of circular RNAs (circRNAs) is a crucial step in understanding their functional impacts. While there are numerous visualization tools available for investigating circRNA interaction networks, these tools are typically limited to known circRNAs from specific databases. Moreover, these existing tools usually require complex installation procedures which can be time-consuming and challenging for users. There is a lack of a user-friendly web application that facilitates interactive exploration and visualization of circRNA interaction networks. CircNetVis is an interactive online web application to enhance the analysis of human/mouse circRNA interactions. The tool allows three different input formats of circRNAs including circRNA IDs from CircBase, circRNA coordinates (chromosome, start position, end position), and circRNA sequences in the FASTA format. It integrates multiple interaction networks for visualization and investigation of the interplay between circRNA, microRNAs, mRNAs and RNA binding proteins. CircNetVis also enables users to interactively explore the interactions of unknown circRNAs which are not reported from previous databases. The tool can generate interactive plots and allows users to save results as output files for offline usage. CircNetVis is implemented as a web application using R-shiny and freely available for academic use at https://www.meb.ki.se/shiny/truvu/CircNetVis/ .", "date": "2024-12-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Nguyen T.-H." }, { "name": "Nguyen H.-N." }, { "name": "Vu T.N." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "Trung Nghia Vu", "email": "TrungNghia.Vu@ki.se", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Thi-Hau Nguyen", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-05-18T14:47:16.635684Z", "lastUpdate": "2024-05-18T14:47:16.638302Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "SerotoninAI", "description": "Serotonergic System Focused, Artificial Intelligence-Based Application for Drug Discovery.\n\nSerotoninAI is a web application for scientific purposes focused on the serotonergic system. By leveraging SerotoninAI, researchers can assess the affinity (pKi value) of a molecule to all main serotonin receptors and serotonin transporters based on molecule structure introduced as SMILES.", "homepage": "https://serotoninai.streamlit.app/", "biotoolsID": "serotoninai", "biotoolsCURIE": "biotools:serotoninai", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3938", "term": "Virtual screening" }, { "uri": "http://edamontology.org/operation_0337", "term": "Visualisation" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3336", "term": "Drug discovery" }, { "uri": "http://edamontology.org/topic_3375", "term": "Drug metabolism" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" }, { "uri": "http://edamontology.org/topic_3373", "term": "Drug development" }, { "uri": "http://edamontology.org/topic_0202", "term": "Pharmacology" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://www.youtube.com/watch?v=MGOwzvvPtxk", "type": [ "Other" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1021/acs.jcim.3c01517", "pmid": "38289046", "pmcid": "PMC11005036", "type": [], "version": null, "note": null, "metadata": { "title": "SerotoninAI: Serotonergic System Focused, Artificial Intelligence-Based Application for Drug Discovery", "abstract": "SerotoninAI is an innovative web application for scientific purposes focused on the serotonergic system. By leveraging SerotoninAI, researchers can assess the affinity (pKi value) of a molecule to all main serotonin receptors and serotonin transporters based on molecule structure introduced as SMILES. Additionally, the application provides essential insights into critical attributes of potential drugs such as blood-brain barrier penetration and human intestinal absorption. The complexity of the serotonergic system demands advanced tools for accurate predictions, which is a fundamental requirement in drug development. SerotoninAI addresses this need by providing an intuitive user interface that generates predictions of pKi values for the main serotonergic targets. The application is freely available on the Internet at https://serotoninai.streamlit.app/, implemented in Streamlit with all major web browsers supported. Currently, to the best of our knowledge, there is no tool that allows users to access affinity predictions for serotonergic targets without registration or financial obligations. SerotoninAI significantly increases the scope of drug development activities worldwide. The source code of the application is available at https://github.com/nczub/SerotoninAI_streamlit.", "date": "2024-04-08T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Lapinska N." }, { "name": "Paclawski A." }, { "name": "Szlek J." }, { "name": "Mendyk A." } ], "journal": "Journal of Chemical Information and Modeling" } } ], "credit": [ { "name": "Jakub Szlęk", "email": "j.szlek@uj.edu.pl", "url": null, "orcidid": "https://orcid.org/0000-0003-1537-9650", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Natalia Łapińska", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-05-18T14:44:32.513056Z", "lastUpdate": "2024-05-18T14:44:32.515105Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "HiPhase", "description": "Jointly phasing small, structural, and tandem repeat variants from HiFi sequencing.", "homepage": "https://github.com/PacificBiosciences/HiPhase", "biotoolsID": "hiphase", "biotoolsCURIE": "biotools:hiphase", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3454", "term": "Phasing" }, { "uri": "http://edamontology.org/operation_3227", "term": "Variant calling" }, { "uri": "http://edamontology.org/operation_3455", "term": "Molecular replacement" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Library" ], "topic": [ { "uri": "http://edamontology.org/topic_3175", "term": "Structural variation" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_0102", "term": "Mapping" } ], "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": "10.1093/bioinformatics/btae042", "pmid": "38269623", "pmcid": "PMC10868326", "type": [], "version": null, "note": null, "metadata": { "title": "HiPhase: jointly phasing small, structural, and tandem repeat variants from HiFi sequencing", "abstract": "Motivation: In diploid organisms, phasing is the problem of assigning the alleles at heterozygous variants to one of two haplotypes. Reads from PacBio HiFi sequencing provide long, accurate observations that can be used as the basis for both calling and phasing variants. HiFi reads also excel at calling larger classes of variation, such as structural or tandem repeat variants. However, current phasing tools typically only phase small variants, leaving larger variants unphased. Results: We developed HiPhase, a tool that jointly phases SNVs, indels, structural, and tandem repeat variants. The main benefits of HiPhase are (i) dual mode allele assignment for detecting large variants, (ii) a novel application of the A*-algorithm to phasing, and (iii) logic allowing phase blocks to span breaks caused by alignment issues around reference gaps and homozygous deletions. In our assessment, HiPhase produced an average phase block NG50 of 480 kb with 929 switchflip errors and fully phased 93.8% of genes, improving over the current state of the art. Additionally, HiPhase jointly phases SNVs, indels, structural, and tandem repeat variants and includes innate multi-threading, statistics gathering, and concurrent phased alignment output generation. Availability and implementation: HiPhase is available as source code and a pre-compiled Linux binary with a user guide at https://github.com/ PacificBiosciences/HiPhase.", "date": "2024-02-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Holt" }, { "name": "Saunders" }, { "name": "Rowell" }, { "name": "Kronenberg Z." }, { "name": "Wenger" }, { "name": "Eberle M." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "James M Holt", "email": "mholt@pacificbiosciences.com", "url": null, "orcidid": "https://orcid.org/0000-0001-6411-9236", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null }, { "name": "Michael Eberle", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-05-18T14:29:08.555278Z", "lastUpdate": "2024-05-18T14:29:08.557627Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" } ] }