Bioinformatics and Computational Genomics
9:00-12:00, February 16th, Thursday
The emergence of the Next Generation Sequencing (NGS) machines revolutionized the genetic research and medical practice. Personalized medicine, based on tailoring the clinical diagnosis and decision making to the patient’s genetic make-up, is believed to be the future of healthcare. Fast and accurate analysis of the genomic information as well as efficient storage techniques are key enablers of the personalized medicine revolution. The session will bring together researchers and students to discuss the latest advances in the fields of computational intelligence and system design and their application to real world problems in bioinformatics and personalized medicine.
The session focuses on four major areas of bioinformatics and computational genomics. First, information theory in bioinformatics, which includes DNA storage and compression. Second, computational intelligence in bioinformatics, which involves gene expression array analysis, molecular sequence alignment and analysis, metabolic pathway analysis, microRNA analysis, phylogenetic, and pattern recognition in bioinformatics. Third, clinical genomics, which incorporates the use of genomic information for diagnosis, cancer stratification for better treatment, drug response and adverse drug reactions prediction. Finally, system design for high performance computational genomics, which encompasses the design of customized hardware, parallel algorithms and large-scale parallel systems for genomic workloads.
Dr. Filippo Utro, Computational Biology Center, IBM T.J. Watson Research
Plant, Population and Cancer Genomics in the DNA revolution
Bringing Genomics to the Bedside
Dr. Filippo Utro
Prof. Saurabh Sinha
Prof. Deming Chen
Invited Student Speaker
Abolfazl Hashemi, University of Texas at Austin
A Tensor Factorization Framework for Haplotype Assembly of Diploids and Polyploids
UIUC Student Speakers
Yang Liu, Learning Structural Motif Representations for Efficient Protein Structure Search
Pei-Chen Peng, Quantitative Modeling of Gene Expression by Using DNA Shape and Accessibility Data
Michael Nute, HIPPI: Highly Accurate Protein Family Classification with Ensembles of HMMs
Vida Ravanmehr, ChIPWig: A New Algorithm for Compression of ChIP-seq Wig Files
Yang Liu won the Best Student Talk award for this session, and was awarded with a genomics ancestry kit.
We thank all our participants for their great research and valuable participation. The judges were impressed with the quality of all talks!