Great Lakes Bioinformatics and the Canadian Computational Biology Collection

By Sarath Chandra Janga, GLBIO/CCBC 2016 Publication Co-Chair

The first joint Great Lakes Bioinformatics and the Canadian Computational Biology Conference 2016 (GLBIO/CCBC) took place in Toronto from May 16th to 19th. The conference was organized by the Great Lakes Bioinformatics Consortium to provide an interdisciplinary forum for the discussion of research findings and methods. An important goal for the conference was to foster long-term collaborative relationships and networking opportunities within the domain of computational approaches to biology. The conference committee accepted twelve full-length original research papers for oral presentations at the conference, nine of which were then submitted for inclusion in the PLOS Collection devoted to the conference

Although this is the 11th Great Lakes Bioinformatics Conference, it also became a venue for the first Canadian Computational Biology conference and attracted 344 total attendees from 11 countries. The conference agenda included eight different workshops on a wide variety of topics including microbiome analysis, best practices in software engineering, machine learning in bioinformatics and next generation sequencing. In addition, it included 14 research sessions and 8 invited keynote speakers providing updates on several exciting areas of research and education, spanning precision medicine, systems biology, public health, open science, metagenomics, gene regulatory networks, evolutionary and synthetic biology. The conference also attracted 168 poster presentations presented in two poster sessions.

Selected papers from the conference paper submissions included in this collection included a new protein classification method, DisPredict2, which employs position specific estimated energy of a residue in protein sequences to segregate disordered from ordered proteins, employing protein-ligand associations and protein interaction network information to boost the success of gene function prediction problem from co-expression associations, expanding the Unifrac Toolbox to empower researchers to extract more varied information from their data, computational approaches for studying associations in sequencing datasets, improved methods and platforms for analyzing and annotating metagenomic datasets, protein localization from microscopy images as well as a modeling study in Escherichia coli proposing flux balance analysis method to uncover transitions in environmental conditions revealing the increasing interest in integrative data mining approaches on multi-omic datasets and employing such datasets for systems biology studies.

The next and 12th GLBio conference will be in the University of Illinois at Chicago from May 22-24, 2017 and we look forward to another exciting conference.

Sarath Chandra Janga is an Assistant Professor in the Department of Biohealth Informatics, School of Informatics and Computing, Indiana University-Purdue University at Indianapolis. He is also a member of the Center for Computational Biology and Bioinformatics, Indiana University’s School of Medicine.