Eric Wasiolek

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"You must be the change you wish to see in the world."
- Mahatma Gandhi

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Master of Science in Computational Molecular Biology

The Computational Molecular Biology Masters was a masters that combines math, computer science, and molecular biology including courses in these subjects.  The degree took three and a half years from 2005 to 2008, two years of classes and one year and a half to complete a 300 paged Masters Thesis done at Stanford that won the "Best Thesis" award in the school of science.  Below are the recommendations, awards, and sample classwork that is a part of this degree.  This degree involved the mathematical and computational analysis of genetic and proteomic sequences as well as the understanding of biomolecular techniques and computer simluations of biological phenomena such as the growth of the brain of C. Elegans as was done in the thesis.  Courses included:  Molecular Biology (I, II, & III), Statistics for Bioinformatics, Bioinformatics, Advanced Bioinformatics (including Chemoinformatics), Courses in C++ including Data Structures, Perl Programming, Graduate Computer Simulation, Neurobiology, Functional Genomics, Developmental Genetics, Stochastic Processes (advanced Math), and others completed with a 3.84 GPA.   This degree prepared me to be able to work not only in the computer industry but also in the biotech industry.  Very few people have this combination of knowledge.

 

Stanford Recommendation

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Best Masters Thesis Award

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Masters Thesis

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Sample Classes

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Sample Classes

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Sample Classes

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Masters Thesis Defense

For a synopsis of the masters thesis (what it is about) click on the link below:

Masters Thesis Defense

This defense explains how a developmental model of the brain of C Elegans was developed and the synaptic pathway analysis tools that analyzed the neural network of that brain.  Finally how synaptic and lineage distance were correlated was discussed.

Masters Thesis Professors

Abstract

A computer program was developed to combine developmental, neural, and genetic information to predict the neural and synaptic development of C. Elegans.  The program divides development into development stages based upon the number of cell divisions required to generate each neuron.  A representation of the synaptic network for each development stage is generated and this represents completely novel information.  Further computational tools were developed to analyze the synaptic network of the developing animal.  These tools find pathways between an input set of sensory neurons and output set of motor neurons to indicate circuit formation and the genetic makeup of circuit formation.  Other tools analyze the number of inputs and outputs through neurons or neuron subpaths indicating high throughput neurons and ganglia worthy of further biological analysis.  Finally, a relationship between development and synapse formation was sought by correlating lineage distance and synaptic distance.

 

Advanced Bioinformatics: Chemoinformatics

ChemoInformatics uses computational tools to analyze chemicals, organic chemicals, biochemical pathways, and drugs.

ChemoInformatics Paper

ChemoInformatics Presentation

 

 

Stochastic Processes

Stochastic Processes

Computer Simulation

 

 

Molecular Biology Papers

These are papers analyzing various molecular biology experiments.

Molecular Biology Paper 1

Molecular Biology Paper 2

Data Structures

 

 
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