Pub Date : 2022-01-01DOI: 10.1093/bioinformatics/btac609
A. Niarakis, J. Thakar, Matteo Barberis, María Rodríguez Martínez, T. Helikar, M. Birtwistle, C. Chaouiya, Laurence Calzone, Andreas Dräger
The Community of Special Interest (COSI) in Computational Modelling of Biological Systems (SysMod) brings together interdisciplinary scientists interested in combining data-driven computational modelling, multi-scale mechanistic frameworks, large-scale -omics data and bioinformatics. SysMod's main activity is an annual meeting at the Intelligent Systems for Molecular Biology (ISMB) conference, a meeting for computer scientists, biologists, mathematicians, engineers and computational and systems biologists. The 2021 SysMod meeting was conducted virtually due to the ongoing COVID-19 pandemic (coronavirus disease 2019). During the 2-day meeting, the development of computational tools, approaches and predictive models was discussed, along with their application to biological systems, emphasizing disease mechanisms. This report summarizes the meeting.
{"title":"Computational modelling in health and disease: highlights of the 6th annual SysMod meeting","authors":"A. Niarakis, J. Thakar, Matteo Barberis, María Rodríguez Martínez, T. Helikar, M. Birtwistle, C. Chaouiya, Laurence Calzone, Andreas Dräger","doi":"10.1093/bioinformatics/btac609","DOIUrl":"https://doi.org/10.1093/bioinformatics/btac609","url":null,"abstract":"The Community of Special Interest (COSI) in Computational Modelling of Biological Systems (SysMod) brings together interdisciplinary scientists interested in combining data-driven computational modelling, multi-scale mechanistic frameworks, large-scale -omics data and bioinformatics. SysMod's main activity is an annual meeting at the Intelligent Systems for Molecular Biology (ISMB) conference, a meeting for computer scientists, biologists, mathematicians, engineers and computational and systems biologists. The 2021 SysMod meeting was conducted virtually due to the ongoing COVID-19 pandemic (coronavirus disease 2019). During the 2-day meeting, the development of computational tools, approaches and predictive models was discussed, along with their application to biological systems, emphasizing disease mechanisms. This report summarizes the meeting.","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"81 1","pages":"4990-4993"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84187010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.1093/bioinformatics/btaa510
Christiana N. Fogg, D. Kovats, R. Shamir
{"title":"2020 ISCB Overton Prize: Jian Peng","authors":"Christiana N. Fogg, D. Kovats, R. Shamir","doi":"10.1093/bioinformatics/btaa510","DOIUrl":"https://doi.org/10.1093/bioinformatics/btaa510","url":null,"abstract":"","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"38 1","pages":"1630-1631"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90609442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-14DOI: 10.1093/bioinformatics/btz849
Pieter Moris, Danh Bui Thi, K. Laukens, P. Meysman
The growing availability of biomolecular networks has led to a need for analysis methods that are able to extract biologically meaningful information from these complex data structures. Here we present MILES (MIning Labeled Enriched Subgraphs), a Java-based subgraph mining tool for discovering motifs that are associated to a given set of nodes of interest, such as a list of genes or proteins, in biomolecular networks. It provides a unique extension to the widely used enrichment analysis methodologies by integrating network structure and functional annotations in order to discern novel biological subgraphs which are enriched in the targets of interest. The tool can handle various types of input data, including (un)directed, (un)connected and multi-label networks, and is thus compatible with most types of biomolecular networks. MILES is available as a platform-independent Java application at https://github.com/pmoris/miles-subgraph-miner alongside a user manual, example datasets and the source code. Supplementary data are available at Bioinformatics online.
{"title":"MILES: a Java tool to extract node-specific enriched subgraphs in biomolecular networks","authors":"Pieter Moris, Danh Bui Thi, K. Laukens, P. Meysman","doi":"10.1093/bioinformatics/btz849","DOIUrl":"https://doi.org/10.1093/bioinformatics/btz849","url":null,"abstract":"\u0000 \u0000 \u0000 The growing availability of biomolecular networks has led to a need for analysis methods that are able to extract biologically meaningful information from these complex data structures. Here we present MILES (MIning Labeled Enriched Subgraphs), a Java-based subgraph mining tool for discovering motifs that are associated to a given set of nodes of interest, such as a list of genes or proteins, in biomolecular networks. It provides a unique extension to the widely used enrichment analysis methodologies by integrating network structure and functional annotations in order to discern novel biological subgraphs which are enriched in the targets of interest. The tool can handle various types of input data, including (un)directed, (un)connected and multi-label networks, and is thus compatible with most types of biomolecular networks.\u0000 \u0000 \u0000 \u0000 MILES is available as a platform-independent Java application at https://github.com/pmoris/miles-subgraph-miner alongside a user manual, example datasets and the source code.\u0000 \u0000 \u0000 \u0000 Supplementary data are available at Bioinformatics online.\u0000","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"252 1","pages":"1978-1980"},"PeriodicalIF":0.0,"publicationDate":"2019-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74898790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-30DOI: 10.7490/F1000RESEARCH.1117436.1
Weronika Puchała, Michał Burdukiewicz, M. Kistowski, K. Dąbrowska, Aleksandra E. Badaczewska Dawid, D. Cysewski, M. Dadlez
{"title":"HaDeX: an R package and web-server for analysis of data from hydrogen-deuterium exchange mass spectrometry experiments","authors":"Weronika Puchała, Michał Burdukiewicz, M. Kistowski, K. Dąbrowska, Aleksandra E. Badaczewska Dawid, D. Cysewski, M. Dadlez","doi":"10.7490/F1000RESEARCH.1117436.1","DOIUrl":"https://doi.org/10.7490/F1000RESEARCH.1117436.1","url":null,"abstract":"","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"1 1","pages":"4516-4518"},"PeriodicalIF":0.0,"publicationDate":"2019-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82396420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Farzin Sohraby, M. J. Moghadam, Masoud Aliyar, Hassan Aryapour
Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased molecular dynamics simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased molecular dynamics simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) molecular dynamics simulations, in this case a protein-ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding’s process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nano-second timescales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction.
{"title":"A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: probing the binding pathway of dasatinib to Src-kinase","authors":"Farzin Sohraby, M. J. Moghadam, Masoud Aliyar, Hassan Aryapour","doi":"10.1101/650440","DOIUrl":"https://doi.org/10.1101/650440","url":null,"abstract":"Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased molecular dynamics simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased molecular dynamics simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) molecular dynamics simulations, in this case a protein-ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding’s process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nano-second timescales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction.","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"119 1","pages":"4714-4720"},"PeriodicalIF":0.0,"publicationDate":"2019-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79013629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-06-01DOI: 10.1093/bioinformatics/btv207
Christiana N. Fogg, D. Kovats
The 23rd Annual International Conference on Intelligent Systems for Molecular Biology and the 14th European Conference on Computational Biology (ISMB/ECCB 2015) is shaping up to be a phenomenal meeting with world-renowned keynote speakers and changes in the conference format that aim to make for a more streamlined and user-friendly conference. The joint ISMB/ECCB conference is held biennially and is the flagship meeting of the International Society for Computational Biology (ISCB). The meeting will take place at the Convention Center Dublin, Ireland from July 10–14, 2015 and will bring together scientists from across the globe working in a broad range of computational biology-related disciplines including genomics, structural biology, proteomics, data mining, machine learning and systems biology. In the past, presentations at the meeting have been organized according to tracks: Proceedings, Highlights and Late Breaking Research tracks. Combined with the multiple track presentation, this caused frustration for attendees when choosing which sessions to attend. In 2015 all oral presentations will be presented in broad theme areas. As in the past, submissions accepted into the highly selective Proceedings track will be published in a special ISMB/ECCB Proceedings issue of Bioinformatics. Conference co-chairs Alex Bateman, Janet Kelso and Desmond Higgins and the conference committee undertook the reorganization effort and came up with five theme areas: Genes, Proteins, Systems, Disease and Data. Batemen said, ‘The idea of themes is an obvious way to organize the talks. But, selecting a small number of themes that represented all computational biology was challenging. Of course many talks will potentially fit across several themes. Time will tell whether these need any tweaking for future meetings’. Kelso believes the new organization will benefit attendees and said, ‘We hope that organizing the meeting more thematically will mean that attendees have an easier time identifying sessions that are relevant and interesting to them’. Five leading scientists have been named as theme chairs and will organize the selection of presentations from each traditional submission cateogry for each theme area. They are Yana Bromberg of Rutgers University (Disease), Janet Kelso of Max Planck Institute (Data), Nicolas Le Novere of the Babraham Institute (Systems), Martin Vingron of the Max Planck Institute for Molecular Genetics (Genes) and Ioannis Xenarios of the University of Lausanne (Proteins). As in the past, the keynote speaker line up features world-class scientists. The speakers include Amos Bairoch of the Swiss Institute of Bioinformatics (ISCB Fellows Keynote), Cyrus Chothia of the MRC Laboratory of Molecular Biology (Senior Scientist Award winner), Eileen Furlong of the European Molecular Biology Laboratory, Curtis Huttenhower of the Harvard T.H. Chan School of Public Health (Overton Prize winner), 2013 Nobel Laureate Michael Levitt of Stanford University and
{"title":"Message from the ISCB: ISMB/ECCB Rebooted: 2015 Brings Major Update to the Conference Program","authors":"Christiana N. Fogg, D. Kovats","doi":"10.1093/bioinformatics/btv207","DOIUrl":"https://doi.org/10.1093/bioinformatics/btv207","url":null,"abstract":"The 23rd Annual International Conference on Intelligent Systems for Molecular Biology and the 14th European Conference on Computational Biology (ISMB/ECCB 2015) is shaping up to be a phenomenal meeting with world-renowned keynote speakers and changes in the conference format that aim to make for a more streamlined and user-friendly conference. The joint ISMB/ECCB conference is held biennially and is the flagship meeting of the International Society for Computational Biology (ISCB). The meeting will take place at the Convention Center Dublin, Ireland from July 10–14, 2015 and will bring together scientists from across the globe working in a broad range of computational biology-related disciplines including genomics, structural biology, proteomics, data mining, machine learning and systems biology. In the past, presentations at the meeting have been organized according to tracks: Proceedings, Highlights and Late Breaking Research tracks. Combined with the multiple track presentation, this caused frustration for attendees when choosing which sessions to attend. In 2015 all oral presentations will be presented in broad theme areas. As in the past, submissions accepted into the highly selective Proceedings track will be published in a special ISMB/ECCB Proceedings issue of Bioinformatics. Conference co-chairs Alex Bateman, Janet Kelso and Desmond Higgins and the conference committee undertook the reorganization effort and came up with five theme areas: Genes, Proteins, Systems, Disease and Data. Batemen said, ‘The idea of themes is an obvious way to organize the talks. But, selecting a small number of themes that represented all computational biology was challenging. Of course many talks will potentially fit across several themes. Time will tell whether these need any tweaking for future meetings’. Kelso believes the new organization will benefit attendees and said, ‘We hope that organizing the meeting more thematically will mean that attendees have an easier time identifying sessions that are relevant and interesting to them’. Five leading scientists have been named as theme chairs and will organize the selection of presentations from each traditional submission cateogry for each theme area. They are Yana Bromberg of Rutgers University (Disease), Janet Kelso of Max Planck Institute (Data), Nicolas Le Novere of the Babraham Institute (Systems), Martin Vingron of the Max Planck Institute for Molecular Genetics (Genes) and Ioannis Xenarios of the University of Lausanne (Proteins). As in the past, the keynote speaker line up features world-class scientists. The speakers include Amos Bairoch of the Swiss Institute of Bioinformatics (ISCB Fellows Keynote), Cyrus Chothia of the MRC Laboratory of Molecular Biology (Senior Scientist Award winner), Eileen Furlong of the European Molecular Biology Laboratory, Curtis Huttenhower of the Harvard T.H. Chan School of Public Health (Overton Prize winner), 2013 Nobel Laureate Michael Levitt of Stanford University and ","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"17 2","pages":"1878-1879"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/bioinformatics/btv207","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72403063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-02-01DOI: 10.1093/bioinformatics/btu415
Y. Bromberg, E. Capriotti
The success of SNP-SIG 2013 (Berlin, Germany), as confirmed by the number of participants and the interesting discussions, indicated the great interest of the community in the automatic annotation of genomic variants. This year the sessions focused on the annotation and prediction of structural/functional impacts of SNPs (morning session) and on the disease and evolution -related SNP perspectives (afternoon session). In the morning session, chaired by Yana Bromberg, the two keynotes were from Ruth Nussinov, National Cancer Institute (Frederick, MD) and Manolis Kellis, Massachusetts Institute of Technology (Cambridge, MA). Dr. Nussinov discussed her investigation of nonsynonymous variants in cancer pathways (here, networks proteins of known 3D structure) to understand the relationship among linked phenomena, e.g. inflammation and cancer. Dr. Kellis addressed the effects of genomic and epigenomic changes on gene regulation. Particularly, he talked about the making predictions of regulatory activity using epigenomic maps of human tissues and specific cell types to expand the annotation of noncoding regions and to provide mechanistic hypotheses of complex disease. This session also hosted four original work presentations by: Christopher Yates, Imperial College of London (London, UK), Lukas Folkman, Griffith University (Brisbane, Australia), Martin Kircher, University of Washington (Seattle, WA), and Bjoern Stade, Christian-Albrechts-University (Kiel, Germany). All presentations described different methods for the annotation and prioritization of single nucleotide variants. After the company presentation (Frank Schacherer, BIOBASE GmbH) and the poster session, Emidio Capriotti chaired the second session to discuss SNPs as effectors of change in disease and evolution. Paul Flicek, European Bioinformatics Institute (Hixton, UK) and Alon Keinan, Cornell University (Ithaca, NY) presented highlight talks in this session. Dr. Flicek focused on the use of comparative genomics analysis to reduce the search space of regulatory variants associated with rare diseases. Particularly, he presented a newly developed method for identifying the thousands of variants in regulatory regions associated with genetic disorders. The major novelty of this method is in the use of functional conservation of regions rather than sequence conservation, which is difficult to detect in non-coding stretched of DNA. Dr. Keinan’s talk presented the results of a population genetics study describing the abundance of rare variants as an effect of the explosive growth of the human population since the Neolithic. The developed theoretical model based on the spectrum of allele frequencies is able to recapitulate the human demographic history. In addition the model has been used to estimate the effects of the load of individual genetic variants in terms of complex disease risk. In the second session there were also three selected presentations by: Graham Ritchie, European Bioinformatics Insti
{"title":"Editor's Choice: SNP-SIG 2013: the state of the art of genomic variant interpretation","authors":"Y. Bromberg, E. Capriotti","doi":"10.1093/bioinformatics/btu415","DOIUrl":"https://doi.org/10.1093/bioinformatics/btu415","url":null,"abstract":"The success of SNP-SIG 2013 (Berlin, Germany), as confirmed by the number of participants and the interesting discussions, indicated the great interest of the community in the automatic annotation of genomic variants. This year the sessions focused on the annotation and prediction of structural/functional impacts of SNPs (morning session) and on the disease and evolution -related SNP perspectives (afternoon session). In the morning session, chaired by Yana Bromberg, the two keynotes were from Ruth Nussinov, National Cancer Institute (Frederick, MD) and Manolis Kellis, Massachusetts Institute of Technology (Cambridge, MA). Dr. Nussinov discussed her investigation of nonsynonymous variants in cancer pathways (here, networks proteins of known 3D structure) to understand the relationship among linked phenomena, e.g. inflammation and cancer. Dr. Kellis addressed the effects of genomic and epigenomic changes on gene regulation. Particularly, he talked about the making predictions of regulatory activity using epigenomic maps of human tissues and specific cell types to expand the annotation of noncoding regions and to provide mechanistic hypotheses of complex disease. This session also hosted four original work presentations by: Christopher Yates, Imperial College of London (London, UK), Lukas Folkman, Griffith University (Brisbane, Australia), Martin Kircher, University of Washington (Seattle, WA), and Bjoern Stade, Christian-Albrechts-University (Kiel, Germany). All presentations described different methods for the annotation and prioritization of single nucleotide variants. After the company presentation (Frank Schacherer, BIOBASE GmbH) and the poster session, Emidio Capriotti chaired the second session to discuss SNPs as effectors of change in disease and evolution. Paul Flicek, European Bioinformatics Institute (Hixton, UK) and Alon Keinan, Cornell University (Ithaca, NY) presented highlight talks in this session. Dr. Flicek focused on the use of comparative genomics analysis to reduce the search space of regulatory variants associated with rare diseases. Particularly, he presented a newly developed method for identifying the thousands of variants in regulatory regions associated with genetic disorders. The major novelty of this method is in the use of functional conservation of regions rather than sequence conservation, which is difficult to detect in non-coding stretched of DNA. Dr. Keinan’s talk presented the results of a population genetics study describing the abundance of rare variants as an effect of the explosive growth of the human population since the Neolithic. The developed theoretical model based on the spectrum of allele frequencies is able to recapitulate the human demographic history. In addition the model has been used to estimate the effects of the load of individual genetic variants in terms of complex disease risk. In the second session there were also three selected presentations by: Graham Ritchie, European Bioinformatics Insti","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"141 1","pages":"449-450"},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77834521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paul Aiyetan, Bai Zhang, Lily Chen, Zhen Zhang, Hui Zhang
Proteome Discoverer is one of many tools used for protein database search and peptide to spectrum assignment in mass spectrometry-based proteomics. However, the inadequacy of conversion tools makes it challenging to compare and integrate its results to those of other analytical tools. Here we present M2Lite, an open-source, light-weight, easily pluggable and fast conversion tool. M2Lite converts proteome discoverer derived MSF files to the proteomics community defined standard - the mzIdentML file format. M2Lite's source code is available as open-source at https://bitbucket.org/paiyetan/m2lite/src and its compiled binaries and documentation can be freely downloaded at https://bitbucket.org/paiyetan/m2lite/downloads.
{"title":"M2Lite: An Open-source, Light-weight, Pluggable and Fast Proteome Discoverer MSF to mzIdentML Tool.","authors":"Paul Aiyetan, Bai Zhang, Lily Chen, Zhen Zhang, Hui Zhang","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Proteome Discoverer is one of many tools used for protein database search and peptide to spectrum assignment in mass spectrometry-based proteomics. However, the inadequacy of conversion tools makes it challenging to compare and integrate its results to those of other analytical tools. Here we present M2Lite, an open-source, light-weight, easily pluggable and fast conversion tool. M2Lite converts proteome discoverer derived MSF files to the proteomics community defined standard - the mzIdentML file format. M2Lite's source code is available as open-source at https://bitbucket.org/paiyetan/m2lite/src and its compiled binaries and documentation can be freely downloaded at https://bitbucket.org/paiyetan/m2lite/downloads.</p>","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"1 2","pages":"40-49"},"PeriodicalIF":0.0,"publicationDate":"2014-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4206089/pdf/nihms614474.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32772539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-01-01DOI: 10.1093/bioinformatics/btt670
G. Crippen, J. Felsenstein, D. Gusfield, S. Karlin, Thomas Lengauer, D. Sankoff
In late 2012, the International Society for Computational Biology (ISCB) and Springer partnered together to enhance the Springer book series in computational biology. The two worked closely together to come up with a strategy to bring to ISCB members and the community at large educational materials that would not only educate the community but also help advance the science. Sponsored by ISCB, the computational biology series publish the latest high-quality research devoted to specific issues in computer-assisted analysis of biological data. The main emphasis is on current scientific developments and innovative techniques in computational biology (bioinformatics), bringing to light methods from mathematics, statistics and computer science that directly address biological problems currently under investigation. The series offer publications that present the state-of-the-art regarding the problems in question, show computational biology/bioinformatics methods at work and discuss anticipated demands regarding developments in future methodology. Titles can range from focused monographs, to undergraduate and graduate textbooks and professional text/reference works. Additionally, ISCB members will receive a 25% discount on book purchases within the series. Springer is seeking to publish quality books in the areas including, but not limited to, databases, data analysis and ontologies; functional and comparative genomics; gene regulation and transcriptomics; protein interactions and networks; data, literature and text mining; molecular sequence analysis; biological networks; sequencing and genotyping technologies; population genetics; systems biology; imaging and visualization; computational proteomics; molecular structural biology; evolution and phylogenetics; metagenomics; biomedical applications; high performance biocomputing; and synthetic biological systems. Book proposal submission details can be found at the book series Web site (http:// www.springer.com/series/5769).
{"title":"ISCB/SPRINGER series in computational biology","authors":"G. Crippen, J. Felsenstein, D. Gusfield, S. Karlin, Thomas Lengauer, D. Sankoff","doi":"10.1093/bioinformatics/btt670","DOIUrl":"https://doi.org/10.1093/bioinformatics/btt670","url":null,"abstract":"In late 2012, the International Society for Computational Biology (ISCB) and Springer partnered together to enhance the Springer book series in computational biology. The two worked closely together to come up with a strategy to bring to ISCB members and the community at large educational materials that would not only educate the community but also help advance the science. Sponsored by ISCB, the computational biology series publish the latest high-quality research devoted to specific issues in computer-assisted analysis of biological data. The main emphasis is on current scientific developments and innovative techniques in computational biology (bioinformatics), bringing to light methods from mathematics, statistics and computer science that directly address biological problems currently under investigation. The series offer publications that present the state-of-the-art regarding the problems in question, show computational biology/bioinformatics methods at work and discuss anticipated demands regarding developments in future methodology. Titles can range from focused monographs, to undergraduate and graduate textbooks and professional text/reference works. Additionally, ISCB members will receive a 25% discount on book purchases within the series. Springer is seeking to publish quality books in the areas including, but not limited to, databases, data analysis and ontologies; functional and comparative genomics; gene regulation and transcriptomics; protein interactions and networks; data, literature and text mining; molecular sequence analysis; biological networks; sequencing and genotyping technologies; population genetics; systems biology; imaging and visualization; computational proteomics; molecular structural biology; evolution and phylogenetics; metagenomics; biomedical applications; high performance biocomputing; and synthetic biological systems. Book proposal submission details can be found at the book series Web site (http:// www.springer.com/series/5769).","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"41 1","pages":"146-147"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82051471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-01-01DOI: 10.1093/bioinformatics/btt673
Jim Cavalcoli, L. Welch, B. Aronow, S. Drăghici, D. Kihara
The International Society of Computational Biology presents: the Great Lakes Bioinformatics Conference, May 16–18, 2014, Cincinnati, Ohio Jim Cavalcoli, Lonnie Welch, Bruce Aronow, Sorin Draghici and Daisuke Kihara University of Michigan (Steering Committee Chair), Ohio University (Steering Committee Chair), Childrens Hospital Medical Center, University of Cincinnati (Conference Chair), Wayne State University (Conference Chair) and Purdue University (Conference Chair)
国际计算生物学学会将于2014年5月16日至18日在俄亥俄州辛辛那提举行:五湖生物信息学会议Jim Cavalcoli, Lonnie Welch, Bruce Aronow, Sorin Draghici和Daisuke Kihara密歇根大学(指导委员会主席)，俄亥俄大学(指导委员会主席)，儿童医院医学中心，辛辛那提大学(会议主席)，韦恩州立大学(会议主席)和普渡大学(会议主席)
{"title":"The International Society of Computational Biology presents: the Great Lakes Bioinformatics Conference, May 16-18, 2014, Cincinnati, Ohio","authors":"Jim Cavalcoli, L. Welch, B. Aronow, S. Drăghici, D. Kihara","doi":"10.1093/bioinformatics/btt673","DOIUrl":"https://doi.org/10.1093/bioinformatics/btt673","url":null,"abstract":"The International Society of Computational Biology presents: the Great Lakes Bioinformatics Conference, May 16–18, 2014, Cincinnati, Ohio Jim Cavalcoli, Lonnie Welch, Bruce Aronow, Sorin Draghici and Daisuke Kihara University of Michigan (Steering Committee Chair), Ohio University (Steering Committee Chair), Childrens Hospital Medical Center, University of Cincinnati (Conference Chair), Wayne State University (Conference Chair) and Purdue University (Conference Chair)","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"110 1","pages":"148-149"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76064929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：