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1.  Education in Computational Biology Today and Tomorrow 
PLoS Computational Biology  2013;9(12):e1003391.
doi:10.1371/journal.pcbi.1003391
PMCID: PMC3861031  PMID: 24348234
2.  Navigating the changing learning landscape: perspective from bioinformatics.ca 
Briefings in Bioinformatics  2013;14(5):556-562.
With the advent of YouTube channels in bioinformatics, open platforms for problem solving in bioinformatics, active web forums in computing analyses and online resources for learning to code or use a bioinformatics tool, the more traditional continuing education bioinformatics training programs have had to adapt. Bioinformatics training programs that solely rely on traditional didactic methods are being superseded by these newer resources. Yet such face-to-face instruction is still invaluable in the learning continuum. Bioinformatics.ca, which hosts the Canadian Bioinformatics Workshops, has blended more traditional learning styles with current online and social learning styles. Here we share our growing experiences over the past 12 years and look toward what the future holds for bioinformatics training programs.
doi:10.1093/bib/bbt016
PMCID: PMC3771234  PMID: 23515468
continuing education; bioinformatics; online learning; massive open online courses (MOOCs)
3.  A decade of web server updates at the bioinformatics links directory: 2003–2012 
Nucleic Acids Research  2012;40(Web Server issue):W3-W12.
The 2012 Bioinformatics Links Directory update marks the 10th special Web Server issue from Nucleic Acids Research. Beginning with content from their 2003 publication, the Bioinformatics Links Directory in collaboration with Nucleic Acids Research has compiled and published a comprehensive list of freely accessible, online tools, databases and resource materials for the bioinformatics and life science research communities. The past decade has exhibited significant growth and change in the types of tools, databases and resources being put forth, reflecting both technology changes and the nature of research over that time. With the addition of 90 web server tools and 12 updates from the July 2012 Web Server issue of Nucleic Acids Research, the Bioinformatics Links Directory at http://bioinformatics.ca/links_directory/ now contains an impressive 134 resources, 455 databases and 1205 web server tools, mirroring the continued activity and efforts of our field.
doi:10.1093/nar/gks632
PMCID: PMC3394264  PMID: 22700703
4.  The 2011 bioinformatics links directory update: more resources, tools and databases and features to empower the bioinformatics community 
Nucleic Acids Research  2011;39(Web Server issue):W3-W7.
The Bioinformatics Links Directory continues its collaboration with Nucleic Acids Research to collaboratively publish and compile a freely accessible, online collection of tools, databases and resource materials for bioinformatics and molecular biology research. The July 2011 Web Server issue of Nucleic Acids Research adds an additional 78 web server tools and 14 updates to the directory at http://bioinformatics.ca/links_directory/.
doi:10.1093/nar/gkr514
PMCID: PMC3125814  PMID: 21715385
5.  CAERUS: Predicting CAncER oUtcomeS Using Relationship between Protein Structural Information, Protein Networks, Gene Expression Data, and Mutation Data 
PLoS Computational Biology  2011;7(3):e1001114.
Carcinogenesis is a complex process with multiple genetic and environmental factors contributing to the development of one or more tumors. Understanding the underlying mechanism of this process and identifying related markers to assess the outcome of this process would lead to more directed treatment and thus significantly reduce the mortality rate of cancers. Recently, molecular diagnostics and prognostics based on the identification of patterns within gene expression profiles in the context of protein interaction networks were reported. However, the predictive performances of these approaches were limited. In this study we propose a novel integrated approach, named CAERUS, for the identification of gene signatures to predict cancer outcomes based on the domain interaction network in human proteome. We first developed a model to score each protein by quantifying the domain connections to its interacting partners and the somatic mutations present in the domain. We then defined proteins as gene signatures if their scores were above a preset threshold. Next, for each gene signature, we quantified the correlation of the expression levels between this gene signature and its neighboring proteins. The results of the quantification in each patient were then used to predict cancer outcome by a modified naïve Bayes classifier. In this study we achieved a favorable accuracy of 88.3%, sensitivity of 87.2%, and specificity of 88.9% on a set of well-documented gene expression profiles of 253 consecutive breast cancer patients with different outcomes. We also compiled a list of cancer-associated gene signatures and domains, which provided testable hypotheses for further experimental investigation. Our approach proved successful on different independent breast cancer data sets as well as an ovarian cancer data set. This study constitutes the first predictive method to classify cancer outcomes based on the relationship between the domain organization and protein network.
Author Summary
It is widely known that cancer is a complex process in which a large number of genes appear to be involved. Through experimental approaches, some oncogenes and tumor suppressors have been identified as playing important roles in the signaling and the regulatory pathways. However, we have not fully understood the complete mechanism of how cancer develops and how it leads to different disease outcomes (aggressive/dangerous or non-aggressive/less-dangerous). In order to identify a list of gene signatures and better predict cancer outcome, we developed an integrated and systematical approach by investigating gene expression profiling alternation caused by disruptions between protein-protein interactions and domain-domain interactions in the human interactome. Our approach achieves the favorable predictive performance if tested on a set of well-documented breast cancer patients, which suggests that the disrupted interactome is important to determine patient prognosis. Our approach is robust if tested on other independent data sets. This work provides a promising prognostic tool to classify different cancer outcomes.
doi:10.1371/journal.pcbi.1001114
PMCID: PMC3068924  PMID: 21483478
6.  Providing web servers and training in Bioinformatics: 2010 update on the Bioinformatics Links Directory 
Nucleic Acids Research  2010;38(Web Server issue):W3-W6.
The Links Directory at Bioinformatics.ca continues its collaboration with Nucleic Acids Research to jointly publish and compile a freely accessible, online collection of tools, databases and resource materials for bioinformatics and molecular biology research. The July 2010 Web Server issue of Nucleic Acids Research adds an additional 115 web server tools and 7 updates to the directory at http://bioinformatics.ca/links_directory/, bringing the total number of servers listed close to an impressive 1500 links. The Bioinformatics Links Directory represents an excellent community resource for locating bioinformatic tools and databases to aid one’s research, and in this context bioinformatic education needs and initiatives are discussed. A complete list of all links featured in this Nucleic Acids Research 2010 Web Server issue can be accessed online at http://bioinformatics.ca/links_directory/narweb2010/. The 2010 update of the Bioinformatics Links Directory, which includes the Web Server list and summaries, is also available online at the Nucleic Acids Research website, http://nar.oxfordjournals.org/.
doi:10.1093/nar/gkq553
PMCID: PMC2896181  PMID: 20542914
7.  Pandora, a PAthway and Network DiscOveRy Approach based on common biological evidence 
Bioinformatics  2009;26(4):529-535.
Motivation: Many biological phenomena involve extensive interactions between many of the biological pathways present in cells. However, extraction of all the inherent biological pathways remains a major challenge in systems biology. With the advent of high-throughput functional genomic techniques, it is now possible to infer biological pathways and pathway organization in a systematic way by integrating disparate biological information.
Results: Here, we propose a novel integrated approach that uses network topology to predict biological pathways. We integrated four types of biological evidence (protein–protein interaction, genetic interaction, domain–domain interaction and semantic similarity of Gene Ontology terms) to generate a functionally associated network. This network was then used to develop a new pathway finding algorithm to predict biological pathways in yeast. Our approach discovered 195 biological pathways and 31 functionally redundant pathway pairs in yeast. By comparing our identified pathways to three public pathway databases (KEGG, BioCyc and Reactome), we observed that our approach achieves a maximum positive predictive value of 12.8% and improves on other predictive approaches. This study allows us to reconstruct biological pathways and delineates cellular machinery in a systematic view.
Availability: The method has been implemented in Perl and is available for downloading from http://www.oicr.on.ca/research/ouellette/pandora. It is distributed under the terms of GPL (http://opensource.org/licenses/gpl-2.0.php)
Contact: francis@oicr.on.ca
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btp701
PMCID: PMC2820679  PMID: 20031970
8.  Evolution in bioinformatic resources: 2009 update on the Bioinformatics Links Directory 
Nucleic Acids Research  2009;37(Web Server issue):W3-W5.
All of the life science research web servers published in this and previous issues of Nucleic Acids Research, together with other useful tools, databases and resources for bioinformatics and molecular biology research are freely accessible online through the Bioinformatics Links Directory, http://bioinformatics.ca/links_directory/. Entirely dependent on user feedback and community input, the Bioinformatics Links Directory exemplifies an open access research tool and resource. With 112 websites featured in the July 2009 Web Server Issue of Nucleic Acids Research, the 2009 update brings the total number of servers listed in the Bioinformatics Links Directory close to an impressive 1400 links. A complete list of all links listed in this Nucleic Acids Research 2009 Web Server Issue can be accessed online at http://bioinfomatics.ca/links_directory/narweb2009/. The 2009 update of the Bioinformatics Links Directory, which includes the Web Server list and summaries, is also available online at the Nucleic Acids Research website, http://nar.oxfordjournals.org/.
doi:10.1093/nar/gkp531
PMCID: PMC2703910  PMID: 19528072
9.  Keeping pace with the data: 2008 update on the Bioinformatics Links Directory 
Nucleic Acids Research  2008;36(Web Server issue):W2-W4.
The Bioinformatics Links Directory, http://bioinformatics.ca/links_directory/, is an online resource for public access to all of the life science research web servers published in this and previous issues of Nucleic Acids Research, together with other useful tools, databases and resources for bioinformatics and molecular biology research. Dependent on community input and development, the Bioinformatics Links Directory exemplifies an open access research tool and resource. The 2008 update includes the 94 web servers featured in the July 2008 Web Server issue of Nucleic Acids Research, bringing the total number of servers listed in the Bioinformatics Links Directory to over 1200 links. A complete list of all links listed in this Nucleic Acids Research 2008 Web Server issue can be accessed online at http://bioinfomatics.ca/links_directory/narweb2008/. The 2008 update of the Bioinformatics Links Directory, which includes the Web Server list and summaries, is also available online at the Nucleic Acids Research website, http://nar.oxfordjournals.org/.
doi:10.1093/nar/gkn399
PMCID: PMC2447757  PMID: 18586831
10.  Conducting Research on the Web: 2007 Update for the Bioinformatics Links Directory 
Nucleic Acids Research  2007;35(Web Server issue):W3-W5.
The Bioinformatics Links Directory, http://bioinformatics.ca/links_directory, is an actively maintained compilation of servers published in this and previous issues of Nucleic Acids Research issues together with many other useful tools, databases and resources for life sciences research. The 2007 update includes the 130 websites highlighted in the July 2007 Web Server issue of Nucleic Acids Research and brings the total number of servers listed in the Bioinformatics Links Directory to just under 1200 links. In addition to the updated content, the 2007 update of the Bioinformatics Links Directory includes new features for improved navigation, accessibility and open data exchange. A complete listing of all links listed in this Nucleic Acids Research 2007 Web Server issue can be accessed online at, http://bioinformatics.ca/links_directory/narweb2007. The 2007 update of the Bioinformatics Links Directory, which includes the Web Server list and summaries is also available online, at the Nucleic Acids Research web site, http://nar.oupjournals.org.
doi:10.1093/nar/gkm459
PMCID: PMC1933129  PMID: 17586821
11.  A compilation of molecular biology web servers: 2006 update on the Bioinformatics Links Directory 
Nucleic Acids Research  2006;34(Web Server issue):W3-W5.
The Bioinformatics Links Directory is a public online resource that lists the servers published in this and all previously published Nucleic Acids Research Web Server issues together with other useful tools, databases and resources for bioinformatics and molecular biology research. This rich directory of tools and websites can be browsed and searched with all listed links freely accessible to the public. The 2006 update includes the 149 websites highlighted in the July 2006 issue of Nucleic Acids Research and brings the total number of servers listed in the Bioinformatics Links Directory to over 1000 links. To aid navigation through this growing resource, all link entries contain a brief synopsis, a citation list and are classified by function in descriptive biological categories. The most up-to-date version of this actively maintained listing of bioinformatics resources is available at the Bioinformatics Links Directory website, . A complete list of all links listed in this Nucleic Acids Research 2006 Web Server issue can be accessed online at . The 2006 update of the Bioinformatics Links Directory, which includes the Web Server list and summaries, is also available online at the Nucleic Acids Research website, .
doi:10.1093/nar/gkl379
PMCID: PMC1538876  PMID: 16845014
12.  The Bioinformatics Links Directory: a Compilation of Molecular Biology Web Servers 
Nucleic Acids Research  2005;33(Web Server issue):W3-W24.
The Bioinformatics Links Directory is an online community resource that contains a directory of freely available tools, databases, and resources for bioinformatics and molecular biology research. The listing of the servers published in this and previous issues of Nucleic Acids Research together with other useful tools and websites represents a rich repository of resources that are openly provided to the research community using internet technologies. The 166 servers highlighted in the 2005 Web Server Issue are included in the more than 700 links to useful online resources that are currently contained within the descriptive biological categories of the Bioinformatics Links Directory. This curated listing of bioinformatics resources is available online at the Bioinformatics Links Directory web site, . A complete listing of the 2005 Nucleic Acids Research Web Server Issue servers is available online at the Nucleic Acids web site, , and on the Bioinformatics Links Directory web site, .
doi:10.1093/nar/gki594
PMCID: PMC1160270  PMID: 15980476
13.  BIND—The Biomolecular Interaction Network Database 
Nucleic Acids Research  2001;29(1):242-245.
The Biomolecular Interaction Network Database (BIND; http://binddb.org) is a database designed to store full descriptions of interactions, molecular complexes and pathways. Development of the BIND 2.0 data model has led to the incorporation of virtually all components of molecular mechanisms including interactions between any two molecules composed of proteins, nucleic acids and small molecules. Chemical reactions, photochemical activation and conformational changes can also be described. Everything from small molecule biochemistry to signal transduction is abstracted in such a way that graph theory methods may be applied for data mining. The database can be used to study networks of interactions, to map pathways across taxonomic branches and to generate information for kinetic simulations. BIND anticipates the coming large influx of interaction information from high-throughput proteomics efforts including detailed information about post-translational modifications from mass spectrometry. Version 2.0 of the BIND data model is discussed as well as implementation, content and the open nature of the BIND project. The BIND data specification is available as ASN.1 and XML DTD.
PMCID: PMC29820  PMID: 11125103
14.  Towards BioDBcore: a community-defined information specification for biological databases 
The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources; and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
doi:10.1093/database/baq027
PMCID: PMC3017395  PMID: 21205783
15.  Towards BioDBcore: a community-defined information specification for biological databases 
Nucleic Acids Research  2010;39(Database issue):D7-D10.
The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
doi:10.1093/nar/gkq1173
PMCID: PMC3013734  PMID: 21097465

Results 1-15 (15)