High Throughput Computational Biology Initiative

Vision

We propose to establish a Center for Excellence in High Throughput Computational Biology. The mission of the center is to conduct fundamental and applied research in modern computational genomics and systems biology arising from the emergence and increasing prominence of high-throughput instrumentation. The center seeks to effectively solve these data-intensive scientific challenges and maintain broad applicability by harnessing emerging computing technologies including cloud computing and inexpensive high performance computing devices such as multicores and GPUs. This combination of high-throughput data-driven biology and high performance computing provides a unique mission to the center that enables it to tackle many challenges of scientific and societal importance.

Approach

The center adopts a three-pronged strategy by focusing on:

1. critical computational challenges arising from the development of new technologies – next-generation DNA sequencing
2. fundamental and long-term research pursuits – systems and synthetic biology driven by heterogeneous data-intensive approaches, and
3. development of bioinformatics methods for advancing technologies designed at Iowa State – microfluidic technologies for phenotypic discovery.

These objectives are realized through multidisciplinary faculty groups in collaboration with external researchers and industrial partners who are at the forefront of technological developments.

Research Thrusts

At the outset, the center focuses on the following broad thematic areas:

Thrust 1: Next-gen sequencing

Next-gen sequencers are being used for many applications — resequencing of individual genomes, sequencing transcriptomes, de novo sequencing of new genomes, metagenomics, polymorphism discovery and population studies, and digital gene expression analysis – thus creating a rich and diverse set of important new computational problems.

Research Plans: We have a track record in developing error correction methods and parallel genome assembly for Illumina sequencers, the most widely used sequencers currently. The center will provide the opportunity to pursue comprehensive development of computational methods for next-gen sequencing technologies.The figure below depicts the problems we will address. It can be thought of as three dimensional with separate dimensions addressing the different next-gen systems, different computing technologies, and different biological applications. Computational methods and bioinformatics tools are needed for every combination of the values along these three dimensions. This is because each next-gen system produces reads with its own distinct characteristics.

Leads: Prof. Srinivas Aluru, Electrical and Computer Engineering, and Prof. Patrick Schnable, Department of Agronomy, also the Director of Center for Plant Genomics and Center for Carbon Capturing Crops.

Thrust 2: Systems Biology

This is aimed at building networks and understanding systems-level behavior through collective and complex interactions of parts.
Research Plans: This research will harness heterogeneous sources of expression data for RNAs/protein/ metabolites obtained from a variety of instrumentation to build robust whole-genome networks. The focus is on the development of computational methods that can collectively analyze large-scale data repositories to take a holistic view as opposed to the current piecemeal approach of restricting the analysis to a few genes or subset of experiments solely due to computational limitations.More specifically, we will do the following: metabolic flux analysis network inference and visualization heterogeneous data integration, and multiscale modeling
Lead:

Thrust 3: Phenomics

While Thrust 1 aims at obtaining the parts list and Thrust 2 focuses on the collective and complex interactions of these parts, phenomics is the grand-scale challenge of linking all of these to function and behavior of organisms.
Research Plans: The center will focus its efforts on the development of confined microfluidic devices for rapid phenotypic discovery at high spatial and temporal resolution, and the development of enabling computational methods and bioinformatics tools.Under this thrust we will also focus on the following: high throughput phenotype measurements lab on a chip greenhouse on a chip
Leads: Prof. Liang Dong and Prof. Santosh Pandey, Electrical and Computer Engineering.