Michael F. Ochs, PhD

B.A., Chemistry, Haverford College               

A.M., Celtic Languages and Literatures, Harvard University

Ph.D., Physics, Brandeis University

Research Interest: Advanced Computational Methods for Genomics Research

Developments over the last 25 years have included knowledge-based statistical and computational methods to address complexity in biological systems.  Initial work led to the development of Bayesian Decomposition, the first nonnegative matrix factorization method applied to genomics data and the first published NMF method in the modern era.  Other work led to a novel method to explore allelic variants that together predispose to genetic disease.  Future developments are focused on spatial transcriptomics and multiomics methods development for elucidating cancer development, especially for pancreatic cancer.

Ochs MF, Stoyanova RS, Arias-Mendoza F, Brown TR. A new method for spectral decomposition using a bilinear Bayesian approach. J Magn Reson. 1999; 137: 161-76.

Moloshok TD, Klevecz RR, Grant JD, Manion FJ, Speier WF, Ochs MF. Application of Bayesian Decomposition for analysing microarray data. Bioinformatics. 2002; 18:566-75.

Wang G, Kossenkov AV, Ochs MF. LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates. BMC Bioinformatics. 2006; 7: 175.

Favorov AV, Andreewski TV, Sudomoina MA, Favorova OO, Parmigiani G, Ochs MF. A Markov chain Monte Carlo technique for identification of combinations of allelic variants underlying complex diseases in humans. Genetics. 2005; 171: 2113-21.

Ochs MF, Rink Lori, Tarn C, Mburu S, Taguchi T, Eisenberg B, Godwin AK. Detection of Treatment-Induced Changes in Signaling Pathways in Gastrointestinal Stromal Tumors Using Transcriptomic Data. Canc Res. 2009; 69: 9125-32.

Ochs MF, Zamani M, Gomes GMR, Neto RCdO, Kane SA. Sneak peek: raptors search for prey using stochastic head turns. The Auk, 2017: 134: 104-115.

Senior Member, IEEE