Anand Sastry

Research Interests

I aim to extract meaningful patterns and information from large biological datasets using various supervised and unsupervised machine learning methods:

  • Developing a sequence-based classifier to accelerate high-throughput protein production
  • Identifying independent regulatory modes in E. coli
  • Analysis and integration of multi-omic data to incorporate transcriptional regulation into constraint-based models

    Education

    University of California, San Diego: PhD student
    Carnegie Mellon University: B.S. with double major in Chemical Engineering and Biomedical Engineering

    Publications

    Sastry A, Monk J, Tegel H, Uhlen M, J. Rockberg, B.O. Palsson, E. Brunk. Machine Learning in Computational Biology to Accelerate High-Throughput Protein Expression. Bioinformatics. 2017. doi:10.1093/bioinformatics/btx207.

    Fang X*, Sastry A*, Tan J, Yurkovich JT, Lloyd CJ, Mih N, Kim D, Yang L, Palsson BO. A high-confidence global transcriptional regulatory network for Escherichia coli is consistent with transcriptomic data. under review.

    Ebrahim A*, Brunk E*, Tan J*, O'Brien EJ, Kim D, Szubin R, Lerman JA, Lechner A, Sastry A, Bordbar A, Feist AM, Palsson BO. Multi-omic data integration enables discovery of hidden biological regularities. Nature Communications. 2016;7:13091. doi:10.1038/ncomms13091.

    Monk J*, Lloyd C*, Brunk E, Mih N, Sastry A, King Z, Takeuchi R, Nomura W, Mori H, Feist AM, Palsson BO. Computable knowledgebase of Escherichia coli metabolism and its structural proteome: Meeting the big data to knowledge challenge. under review.

    Prior Work Experience

    Software Consultant, Novo Nordisk Foundation Center for Biosustainability
    San Diego, CA. Oct 2014-May 2015

  • Software development of the MASS Toolbox kinetic modeling package

    Development Engineer, Emerald Therapeutics
    Menlo Park, CA. Summer 2013 & 2014

  • Developed various tools in Mathematica to facilitate laboratory automation
  • Designed and implemented an automated process to to cleave biopolymers from resin

    Contact Information

    Email Address: avsastry@eng.ucsd.edu
    LinkedIn: http://www.linkedin.com/in/anandsastry

  • Location

    Location

    417 Powell-Focht Bioengineering Hall

    9500 Gilman Drive La Jolla, CA 92093-0412

    Contact Us

    Contact Us

    In Silico Lab:  858-822-1144

    Wet Lab:  858-246-1625

    FAX:   858-822-3120

    Website Concerns: sbrgit@ucsd.edu

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