Topic: Bioinformatics Software

Abstract:
Phenotypic heterogeneity in cancer is often caused by different patterns of genetic alterations. Understanding such phenotype-genotype relationships is fundamental for the advance of personalized medicine. In this talk, I will present a computational method, named NETPHIX (NETwork-to-PHenotype association with eXclusivity) to identify subnetworks of genes whose genetic alterations are associated with drug response or other continuous cancer phenotypes. Leveraging interaction information among genes and properties of cancer mutations such as mutual exclusivity, we model the problem as a variant of connected set cover and obtain a subnetwork of associated genes using integer linear program (ILP) optimization. Applied to a large-scale drug screening dataset, NETPHIX uncovered gene modules significantly associated with responses for many drugs. We show that the identified modules provide important insights into drug action and can also be leveraged to suggest drug combinations.

Bio:
Dr. Yoo-Ah Kim is a staff scientist in the National Center for Biotechnology Information at National Institutes of Health (NCBI/NLM/NIH). Her current research focuses on algorithmic approaches in cancer network biology. Before joining NIH in 2008, she received her PhD degree in Computer Science from the University of Maryland, College Park in 2005 and was with the CSE department at the University of Connecticut, working on combinatorial optimization and graph algorithms.

Registration:
https://cbiit.webex.com/cbiit/onstage/g.php?MTID=e968a58127acdb59b961e2ef13865c7ad

Description:

This workshop will focus on the analysis of Next Generation Sequencing (NGS) data using the program MacVector. It will cover alignment/assembly of NGS data to one or more reference sequences for RNA expression analysis, and Single Nucleotide Polymorphism (SNP) detection and/or sequence confirmation. It will also cover de novo assembly of short read (Illumina or IonTorrent) and/or long read (Sanger, PacBio or Oxford Nanopore) data for both modest sequences and for entire genomes. Learn how to use MacVector to identify and extract subsets of paired-end reads from large data sets, enabling focus on just those related to your project.

Speaker: Dr. Kevin Kendal, Field Application Scientist

For questions, contact Dr. Daoud Meerzaman.

Registration:
https://cbiit.webex.com/cbiit/onstage/g.php?MTID=ec7d9bf4c9b10ea1a5dd4ba4383bfede7

Although much MacVector functionality is targeted at DNA analysis, a large number of features also exist for creating, annotating and analyzing protein sequences. This workshop will cover this functionality in depth. Topics include translating DNA into protein sequences, reverse-translating proteins into DNA and optimizing codon usage, analyzing protein sequences for active sites, and other steps in the analysis process. Dr. Kendal also will demonstrate search functions, including BLAST and local searches, and offer tips for extracting subsets of NGS reads that encode a specific protein.

Speaker: Dr. Kevin Kendal, Field Application Scientist

For questions, contact Dr. Daoud Meerzaman.