Brion Sarachan

ME, Electrical, Computer, and Systems Engineering (Rensselaer Polytechnic Institute) BE, Electrical Engineering (University of Rochester)

Brion Sarachan has over thirty years experience architecting, prototyping and developing software, with some notable early work in television broadcasting and then focused on bioinformatics and life sciences for more than half this time. Brion is currently focused on software for GE's Renewable Reservoir for energy storage and also developing software for cancer researchers under a grant from the National Cancer Institute (UO1CA204826-01 – Informatics Tools for Tumor Heterogeneity in Multiplexed Fluorescence Images).

We are like tenant farmers chopping down the fence around our house for fuel when we should be using nature’s inexhaustible source of energy – sun, wind and tide. I’d put my money on the sun and solar energy. What a source of power! I hope we don’t have to wait until oil and coal run out before we tackle that.

Thomas Edison
  1. 1998 timeline
    1998
    Led development of NBC’s digital broadcast system, on-air 20+ years
  2. 2001 timeline
    Launched GE’s Bioinformatics Lab
    2001
  3. 2001 timeline
    2001
    Taught Computer Science at RPI as Adjunct Assistant Professor
  4. 2016 timeline
    Co-PI on Nat’l Cancer Institute ITCR program on Tumor Heterogeneity
    2016
  5. 2019 timeline
    2019
    Leading software team for Renewable Reservoir
Just for fun
Just for fun

Brion has published a few games in the popular app stores.

Publications
  1. Kumar, V.S., Williams, J.W., Aggour, K.S., Sarachan, B., Al-Kofahi, Y. and Santamaria-Pang, A., 2015. Collaborative Analysis of High-Content Image Data. In NIST BioImage Informatics Conference.
  2. Spagnolo, D.M., Gyanchandani, R., Al-Kofahi, Y., Stern, A.M., Lezon, T.R., Gough, A., Meyer, D.E., Ginty, F., Sarachan, B., Fine, J. and Lee, A.V., 2016. Pointwise mutual information quantifies intratumor heterogeneity in tissue sections labeled with multiple fluorescent biomarkers. Journal of Pathology Informatics, 7: 47.
  3. Spagnolo, D.M., Al-Kofahi, Y., Zhu, P., Lezon, T.R., Gough, A., Stern, A.M., Lee, A.V., Ginty, F., Sarachan, B., Taylor, D.L. and Chennubhotla, S.C. 2017. Platform for quantitative evaluation of spatial intratumoral heterogeneity in multiplexed fluorescence images. Cancer Research, 77(21), pp.e71-e74.
  4. Spagnolo, D.M., Al-Kofahi, Y., Zhu, P., Lezon, T.R., Gough, A., Stern, A.M., Lee, A.V., Ginty, F., Sarachan, B., Taylor, D.L. and Chennubhotla, S.C., 2017. Platform for quantitative evaluation of spatial intratumoral heterogeneity in multiplexed fluorescence images. Cancer research, 77(21), pp.e71-e74.
  5. Gerdes, M.J., Sevinsky, C.J., Sood, A., Adak, S., Bello, M.O., Bordwell, A., Can, A., Corwin, A., Dinn, S., Filkins, R.J. and Hollman, D., 2013. Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue. Proceedings of the National Academy of Sciences, 110(29), pp.11982-11987.

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