Vancouver Bioinformatics User Group (VanBUG)

Art Poon

dev — Fri, 08 Feb 2013 08:00:31 +0000

Talk Title:
Reconstructing the evolution of HIV within a patient

Date/Time:
Thursday, March 7th, 2013, 6:00 pm

Affiliation:
Assistant Professor (Partner) - UBC Department of Medicine
Associate Research Scientist, British Columbia Centre for Excellence in HIV/AIDS
Adjunct Assistant Professor - Simon Fraser University, Faculty of Health Sciences

URL:
Art Poon

Abstract:
HIV evolves very rapidly because it makes frequent errors as it copies its genome to produce new viruses. For this reason, it has been difficult to develop an effective anti-HIV vaccine, as the incoming HIV genome can look very different from one infection to another. The rapid mutation of HIV genomes also causes an infection to proliferate into a highly diverse population within a single patient, and enables the virus to escape the immune system. Recent innovations in genome sequencing technology (known as “next-generation sequencing”) are providing us with the tools necessary to grapple with the extensive variation of HIV. However, the massive size and complexity of these sequence data presents a new bioinformatic challenge to HIV biologists. In my research, I am developing new software tools to extract key information from next-generation sequencing data to address critical problems in HIV treatment and prevention. I will show how these data can be used to determine when a patient became infected by HIV, what the initial HIV genome looked like, and how we can reconstruct a detailed history of how an infection has evolved over time.

Please note:
Trainees are invited to meet with the VanBUG speaker for open discussion of both science and career paths. This takes place 4:30-5:30pm in either the Boardroom or Lunchroom on the ground floor of the BCCRC

Recommended Readings

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Introductory Speaker:
Matthew Whiteside, PhD candidate, Brinkman Lab, Simon Fraser University

Title:
Improving the Performance of Computational Ortholog Prediction

Bonnie Kirkpatrick

dev — Tue, 05 Feb 2013 19:51:05 +0000

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Presentation:
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Talk Title:
Biological Models with Combinatorial Spaces

Date/Time:
Thursday, February 7th, 2013, 6:00 pm

Affiliation:
Postdoctoral Researcher at University of British Columbia

URL:
Bonnie Kirkpatrick

Abstract:
Probabilistic models are common in biology. Many of the successful models have been readily tractable, leaving calculations on models with a combinatorial-sized state space as an open problem. This talk examines two kinds of models with combinatorial state spaces: continuous-time and discrete-time Markov chains. These models are applied to two problems: RNA folding pathways and family genetics. While the applications are disparate topics in biology, they are related via their models, the statistical quantities of interest, and in some cases the computational techniques used to calculate those quantities.

Recommended Readings

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Introductory Speaker:
Gavin Ha, PhD candidate, Shah Lab, BC Cancer Research Centre

Title:
Probabilistic approach to detect subclonal copy number and LOH from heterogeneous cell populations in whole genome sequencing of tumour biopsies

Ben Raphael

dev — Thu, 08 Nov 2012 23:51:08 +0000

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Talk Title:
Computational Analysis of Mutational Heterogeneity in Cancer Genomes

Date/Time:
Thursday, November 8th, 2012, 6:00 pm

Affiliation:
Associate Professor of Computer Science, Brown University

URL:
Raphael Lab

Abstract:
Recent sequencing projects have demonstrated that somatic mutations in cancer genomes are highly heterogeneous. This mutational heterogeneity is apparent on two levels. First, individual cells within a tumor typically have different complements of somatic mutations. Second, different individuals with the same type of cancer often exhibit different combinations of causal, or driver, mutations. We describe algorithms to address both of these sources of heterogeneity. In the first case, we present an algorithm to infer clonal and subclonal copy number aberrations in the presence of admixture by normal (non-cancerous) cells. In the second case, we describe two algorithms to identify driver pathways, groups of genes containing driver mutations, in a large cohort of cancer samples. The first algorithm, HotNet, uses prior information about interactions between genes and identifies subnetworks of a genome-scale interaction network that are recurrently mutated. The second algorithm, Dendrix, optimizes a measure derived from the statistical properties of mutations on driver pathways. We apply these algorithms to genome/exome sequencing and array copy number data from several cancer types in The Cancer Genome Atlas (TCGA). We identify both known pathways and novel combinations of mutations, the latter suggesting previously uncharacterized interactions, or crosstalk between pathways.

Recommended Readings

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Introductory Speaker:
Andrew Roth, PhD candidate, Shah Lab, BC Cancer Research Centre

Title:
Studying The Evolutionary Dynamics Of Cancer Using Next Generation Sequencing

Robert Balshaw

dev — Thu, 18 Oct 2012 22:11:17 +0000

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Talk Title:
A Biostatistician’s Take on Biomarkers

Date/Time:
Thursday, October 18th, 2012, 6:00 pm

Affiliation:
Senior Scientist, Statistician, Communicable Disease Prevention and Control Services (CDPACS), BC Centre for Disease Control

URL:
Robert Balshaw

Abstract:
The traditional training of a biostatistician ill prepares one to encounter the enormous datasets and science-fiction technologies that arise during the search for biomarkers. In my talk I will describe a few of the interesting projects I have had the good luck work on over the last few years and how biomarkers have become recurring theme in my work. Along the way, I will discuss some of the ways that Bioinformatics and Biostatistics may cross-pollinate with one another in the search for and validation of new biomarkers.

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Introductory Speaker:
Kieran O’Neill, PhD candidate, Brinkman Lab, BC Cancer Research Centre

Title:
Deep Phenotyping of Multitube Flow Cytometry Data Reveals New Cell Types Associated with NPM1 Mutation in AML

Katherine Pollard

dev — Mon, 17 Sep 2012 16:16:16 +0000

PIMS-sponsored speaker

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Talk Title:
Quantifying taxonomic and functional diversity of metagenomes from next-generation sequencing data

Date/Time:
Thursday, September 13th, 2012, 6:00 pm

Affiliation:
Associate Investigator - Gladstone Institutes
Associate Professor - Department of Epidemiology & Biostatistics, Institute for Human Genetics, and Institute for Computational Health Sciences
University of California, San Francisco

URL:
Pollard Group

Abstract:
Analysis of shotgun sequenced environmental DNA, known as metagenomics, promises insight into the taxonomic and functional composition of microbial communities. To overcome challenges associated with the fragmentary, non-overlapping nature of metagenomic sequence data, we developed novel statistical phylogenetic methods for de novo identification of operational taxonomic units (OTUs) and operational protein families (OPFs). To test the performance of these and other metagenomics analysis tools, we developed read-based error detection methods and a simulation pipeline. Two key features of our approach are the use of probabilistic models of gene family evolution (e.g., profile hidden Markov models and stochastic context free grammars) and the generation of phylogenetic trees in which each leaf is a metagenomic sequencing read from a particular gene family. We applied our analysis tools to identify novel bacteria and to quantify the diversity of microbial communities from the world’s oceans and the human gut.

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Introductory Speaker:
Luisa Chan, MSc candidate, Brinkman Lab, Simon Fraser University

Title:
Whole-genome transcriptome analysis of 5’-triphosphate and 5’-monophosphate RNAs in Pseudomonas aeruginosa strain PAO1

20df

Phil Bourne

dev — Tue, 20 Mar 2012 18:02:57 +0000

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Presentation
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Talk Title:
What Really Happens When We Take a Drug?

Date/Time:
Thursday, April 12th, 2011, 6:00 pm

Affiliation:
Professor, Department of Pharmacology and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego
Associate Director, RCSB Protein Data Bank and Adjunct Professor, Burnham Institute

URL:
Philip E. Bourne
The Bourne Lab

Abstract:
This is a question which, after generic clinical trials, is still very much answered by observing patient outcomes. Methods from bioinformatics and systems biology are making some inroads into answering this question more systematically through integration of a variety of data sources and important algorithmic developments. I will dig in to some of our work in this area, but if you cant wait refer to Xie et al. (2012) Annual Review of Pharmacology and Toxicology 52: 361-379. I’ll also describe the importance of open science to this collective effort.

Recommended Readings
Ten Simple Rules

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Introductory Speaker:
Andrew McPherson, PhD candidate, Sahinalp lab, SFU and Huntsman lab, UBC

Title: Predicting the complex origins of chimeric transcripts using nFuse

Nathan Price

dev — Mon, 05 Mar 2012 21:40:56 +0000

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Talk Title:
Integrated modeling of metabolic and regulatory networks

Date/Time:
Thursday, March 8th, 2011, 6:00 pm

Affiliation:
Associate Professor, Institute for Systems Biology, Seattle, WA

URL:
Nathan Price

Abstract:
To harness the power of genomics, it is essential to link genotype to phenotype through the construction of quantitative systems models. I will discuss approaches for the creation of such quantitative models that can simulate a variety of cellular functions. I will focus particularly on automated methods for integrating metabolic and regulatory networks such as our newly developed approach, Probabilistic Regulation of Metabolism (PROM) (Chandrasekaran and Price, PNAS, 2010). PROM is notable in that it represents the successful integration of a top-down reconstructed, statistically inferred regulatory network with a bottom-up reconstructed, biochemically detailed metabolic network, bridging two important classes of systems biology models that are rarely combined quantitatively. Additionally, I will discuss our new strategy to curate the inference of regulatory interactions from high throughput data using metabolic networks—providing multiple layers of biological context to the problem of regulation. Finally, I will describe our approach to building tissue and cell type specific metabolic models, which we have now done for 131 different cell types and tissues in the human body.

Recommended Readings
Modeling of genome-scale metabolic and regulatory networks

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Introductory Speaker:
Evan Morien, MSc candidate, Pavlidis lab, CHiBi, UBC

Title: Genomic Expression Patterns in WIld Pacific Salmon

William Hsiao

dev — Thu, 09 Feb 2012 19:36:54 +0000

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Presentation:
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Talk Title:
Microbial Genomics, Pangenomics, and Metagenomics in Disease and in Health

Date/Time:
Thursday, February 9th, 2011, 6:00 pm

Affiliation:
Bioinformatician, BCCDC Public Health Microbiology & Reference Laboratory

Abstract:
As DNA sequencing technologies continue to improve, sequencing of microbial genomes can now be done routinely. We have gone from a group of researchers spending years to generated and study one bacterial genome to an individual researcher comparing tens or hundreds of similar genomes at a time with the help of bioinformatic applications. Pangenomic analysis allows us to decipher how a bacterium evolves and how certain small mutations could have a large impact on disease outcome. In recent years, we have also started to sequence the genetic material directly isolated from a microbial community (microbiota) in order to bypass culturing. The International Human Microbiome Consortium and associated efforts are trying to decipher the interactions between our bodies and our microbiotas. The metagenomics approach allows researchers to study an entire microbial community in relation to health and diseases but new challenges arise on how to assign taxonomic and functional information to incomplete and sometimes novel sequences. With the increased scale of sequencing, new bioinformatics and statistical tools are needed to facilitate data process and interpretation. In this talk, I’ll discuss the progress and challenges of microbial genomic analysis with examples drawn from my own research and from literature. Through this talk, I wish to demonstrate that microbial genomics has benefit greatly from the technological improvements over the years and there is a bright future in applying microbial genomics to improve human health.

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Introductory Speaker:
Warren Cheung, PhD candidate, Wasserman lab, CMMT

Title: Biomedical Topic Profiles from Bibliographical Literature Evidence

François Major

dev — Fri, 09 Dec 2011 05:04:00 +0000

PIMS-sponsored speaker

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Talk Title:
Simulating and Predicting the MicroTargetome

Date/Time:
Thursday, December 8th, 2011, 6:00 pm

Affiliation:
Institut de Recherche en Immunologie et en Cancérologie and Département d’Informatique et de Recherche Opérationnelle, Université de Montréal

URL:
François Major

Abstract:
Protein output determines cell types and states. In animals, microRNAs (miRNAs) are key actors in controlling protein output. Mature miRNAs are about 22-nucleotide long. They are loaded in RNA-induced silencing complexes (RISCs), which bind to miRNA complementary sites in messenger RNAs (mRNAs) to repress their translation. Besides, recent studies indicate that various non-coding RNAs control protein output by competitive attraction of miRNAs. I will present an algorithm to predict the microTargetome, i.e. the RISC/mRNA matching, which considers all competing endogenous RNAs (ceRNAs). The model uses a free-energy of hybridization, and an algorithm that mimics miRNA competition and cooperation. Using this algorithm, we simulated the overexpression of single miRNAs in a specific cell line, and derived a series of biological consequences related to such a protein expression control system. MiRNA, ceRNA, and mRNA levels vary in different cell types and states, including cancer cells. Understanding and predicting microTargetome changes could thus bring insights into the role of RNA in cell differentiation, as well as in cancer development and progression.

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Introductory Speaker:
Fong Chun Chan, MSc candidate, Gascoyne Lab, BC Cancer Research Centre

Title:
Detection of Differentially Expressed Alternative Transcripts using Conventional Microarrays

Paul Pavlidis

dev — Thu, 17 Nov 2011 17:26:25 +0000

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Presentation:
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Talk Title:
The ruin of gene network analysis by multifunctionality

Date/Time:
Thursday, November 17th, 2011, 6:00 pm

Affiliation:
Associate Professor, Department of Psychiatry, University of British Columbia and Member of the Brain Research Centre

URL:
Paul Pavlidis

Abstract:
A major goal of biology is to identify the functional relationships and interactions among genes and apply this knowledge to make predictive models. In bioinformatics, it is now routine to use various types of gene network and gene function information to interpret
high-throughput experiments. Examples include “GO enrichment”, network-motivated clustering or gene function prediction methods (e.g. “guilt by association”) and candidate gene prioritization methods. I will describe how a phenomenon we call “gene multifunctionality” distorts such analyses. Genes having high multifunctionality are the source of serious biases or artifacts that can distract attention from more interesting signals, cause
misleading results in algorithm evaluations, and generally make meaningfully applying known information on gene function extremely difficult. I will argue that this problem is ignored at our peril, and suggest some possible remedies and strategies for making progress.

Please note:
Trainees are invited to meet with the VanBUG speaker for open discussion
of both science and career paths. This takes place 4:30-5:30pm in either
the Boardroom or Lunchroom on the ground floor of the BCCRC

——————————

Introductory Speaker:
Rebecca Worsley Hunt, PhD candidate, Wasserman Lab at Centre for Molecular Medicine and Therapeutics (CMMT)

Title:
Genome nucleotide composition and sequence length affect over-representation predictions of transcription factor binding sites in ChIP-based experiments