Difference between revisions of "User:Msamdars"

From LMU BioDB 2019
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(Research Experience)
(Research Experience)
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==== Department of Bioengineering, University of California – San Diego====
 
==== Department of Bioengineering, University of California – San Diego====
 +
 
San Diego, CA
 
San Diego, CA
 +
 
``(June 2019 – August 2019)``
 
``(June 2019 – August 2019)``
 +
 
Advisors: Dr. Jeff Omens & Ariel Wang
 
Advisors: Dr. Jeff Omens & Ariel Wang
 +
 
Computational fibrosis model of interactions between myofibroblasts and macrophages mediated by compound 43
 
Computational fibrosis model of interactions between myofibroblasts and macrophages mediated by compound 43
 
* Created a specialized program in Python in order to simulate sets of ordinary differential equations meant to represent two cells, cardiac fibroblasts and M1/M2-type macrophages
 
* Created a specialized program in Python in order to simulate sets of ordinary differential equations meant to represent two cells, cardiac fibroblasts and M1/M2-type macrophages

Revision as of 14:03, 30 August 2019

Mihir Samdarshi

This page is under construction.

Contact Information

Snail Mail:

1 LMU Drive, MSB-5848
Los Angeles, CA 90045

email:

msamdars(at)lion.lmu(dot)edu

Education

Loyola Marymount University

Location: Los Angeles, CA

Degree: Bachelor's of Science

Major: Biology

Minor: Computer Science

Anticipated Graduation: December, 2019


Related Courses

Biology Computer Science
  • Molecular Biology of the Genome ¹
  • General Microbiology ¹
  • Urban Ecology ¹
  • Plant Biotechnology
  • General Physiology
  • Epidemiology
  • Genetics Laboratory ¹


¹ signifies that the course was a lab course or taken concurrently with a lab version of the course

  • Computer Programming
  • Programming Lab
  • Data Structures
  • Algorithms
  • Interaction Design
  • Programming Languages

Research Experience

LMU Bioinformatics and Biomathematics Group, Loyola Marymount University

Los Angeles, CA (September 2015 – Present) Advisors: Dr. Kam Dahlquist & Dr. John David Dionisio

GRNSight: Web app and service for visualizing models of gene regulatory networks. https://dondi.github.io/GRNsight/

  • Currently the senior-most member of lab, in charge of supervising three other members and leading the major release initiative
  • Combined knowledge of genetics and biology with computer science to create innovative visualization tool for small-scale gene regulatory networks
  • Gained valuable experience working with Javascript, HTML5/CSS3, Python, Node.js, D3.js, Bootstrap, ReactJS, Jekyll, Mocha, Chai, GitHub, Linux, and Photoshop
  • Worked on refactoring codebase, implementing test-driven development practice, and adding new functions
  • Assisted with time-course experiments measuring yeast gene expression using DNA microarrays

Department of Bioengineering, University of California – San Diego

San Diego, CA

``(June 2019 – August 2019)``

Advisors: Dr. Jeff Omens & Ariel Wang

Computational fibrosis model of interactions between myofibroblasts and macrophages mediated by compound 43

  • Created a specialized program in Python in order to simulate sets of ordinary differential equations meant to represent two cells, cardiac fibroblasts and M1/M2-type macrophages
  • Gained valuable experience working in Python, utilizing open source packages like Pandas, Matplotlib, Numpy, and more

Redox Biology Center, University of Nebraska-Lincoln

Lincoln, NE ``(June 2018 – August 2018)`` Advisors: Dr. Jiri Adamec & Ryan Grove

Mathematical model of neuronal energy metabolism pathways affected in epilepsy.

  • Used common computational/mathematical biology tools to create a mathematical model of energy metabolism in neurons and astrocytes
  • Created and executed various wet lab experiments with C. elegans in order to validate the results of the mathematical model; used a thrashing assay to quantify and compare results between various trials with differing variables
  • Gained valuable experience working with MATLAB, COPASI, Cell Designer, and various MATLAB modeling packages like Recon 3D.