Abhik Shah
PhD candidate in Bioinformatics
Systems & Synthetic Biology Group
University of Michigan

abhikshah@gmail.com
umich.edu/~shahad
ano.malo.us

I work with Dr. Peter Woolf in developing machine learning methods to learn mechanisms from biological data and knowledge. My methods and software use Bayesian networks to simulate complex biological systems using probabilistic and nonlinear models.

I am completing my dissertation tentatively titled Mechanistic Bayesian Networks for Biological Modeling and expect to graduate in August 2009.

Shah A, Keshamouni V, Woolf P.
Validating protein and miRNA interaction networks using expression data.
In Preparation, 2009.

Shah A, Tenzen T, McMahon A, Woolf P.
Using Mechanistic Bayesian Networks to Identify the Downstream Targets of Sonic Hedgehog Pathway.
In Preparation, 2009.

Shah A, Woolf P.
Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data.
Journal of Machine Learning Research. 10(Feb):159-162, 2009.
abstract / pdf / bibtex / RIS / mloss.org

Draghici S, Khatri P, Shah A, Tainsky M.
Assessing the Functional Bias of Commercial Microarrays Using the Onto-Compare Database.
Biotechniques, 2003.
abstract / pdf / bibtex / RIS

Draghici S, Khatri P, Bhavsar P, Shah A, Krawetz S, Tainsky M.
Onto-Tools, the Toolkit of the Modern Biologist: Onto-Express, Onto-Compare, Onto-Design and Onto-Translate.
Nucleic Acids Research, 2003.
abstract / pdf / bibtex / RIS


Application and python library for learning Bayesian networks from data. It's opensource and has features unmatched by similar software. Documentation and software available at code.google.com/p/pebl-project.

anyCloud


Framework for distributed computing using a variety of clusters, grids and cloud computing platforms. Seamlessly run the same code on multiple cores and processors, an IPython cluster, an Apple XGrid and Amazon EC2 by changing a few configuration parameters. Alpha quality software available at code.google.com/p/anycloud.


A prototype web application for iteratively learning and improving Bayesian networks. Integrated with Sakai-based portal for authentication and data importing. Provided a novel javascript network viewer. Screenshots coming soon.

Curriculum Vitae in TXT and PDF formats.
Updated Feb 01, 2009.