#### Undergaduate Program on Genomic Sciences

##### National Autonomous University of Mexico (UNAM)

Av. Universidad

Cuernavaca, Morelos 62100

Ramon Betancourt 342 Cell phone: (52) (312) 1442079

Villa de Álvarez, Colima 28984 Email: rrodrigu@lcg.unam.mx

Av. Universidad

Cuernavaca, Morelos 62100

Intern

Duties included:

- Reproducing the metabolic model of Karp, P. D. et al (2014)
*. A genome-scale metabolic flux model of Escherichia coli K–12 derived from the EcoCyc database.* - Studying Enzyme localization in the context of FBA model of
*Escherichia col**i.* - Constructing the Transcription Factor - Enzyme network using metabolic and gene regulatory data.
- Developing a
*Bacillus subtilis*model that integrates metabolism and transcriptional regulation. - Running multiple simulations of the previous model to compare the simulated results with experimental data.
- Studying Enzyme localization in the context of the metabolic model of
*Bacillus subtilis**.*

Skills developed:

- Using and Retrieving metabolic data from Pathway Genome Data Bases.
- Developing parsing tools (Perl and Python) to clean and manage metabolic and regulatory data.
- Using Pathway Tools software (a systems biology software) to retrieve metabolic data.
- Using linear programming software in R.
- Acquiring more in-depth understanding about Flux Balance Analysis (FBA).
- Managing metabolic tools in Matlab (Cobra toolbox) and Python (Cobrapy).
- Using tools derived from FBA: pFBA, FVA, Mapping fluxes.
- Developing python software to construct a metabolic + transcriptional regulation model.
- Using Cytoscape.
- Acquiring statistical skills and using statistical libraries (Fisher Test, Pearson correlation, Linear regression).

Intern

Duties included:

- Programming an ODE-based model that describes plasmid dynamics in a bacterial population under different treatments of antibiotics.

- Programming a numerical method (Bisection method) to find the rate of horizontal gene transfer that makes a plasmid persist without antibiotics.
- Developing an application of the Gillespie Algorithm to study the growth of bacterial population in a chemostat.
- Improving speed of the previous algorithm adapting it to the tau-leap method.
- (In progress) Studying machine learning algorithms and try to predict the optical density of a bacterial population at the end of the day, using experimental data (13 days and different treatments with antibiotics).

Skills developed:

- R programming.
- Programming a numerical method to solve a biological problem.
- Developing an application of the Gillespie Algorithm.
- Using Knn algorithm as machine-learning algorithm.

1. Rafael Peña-Miller, Rogelio Rodríguez-González, Craig R MacLean and Alvaro San Millan (2015). "Evaluating the effect of horizontal transmission on the stability of plasmids under different selection regimes". *Mobile Genetics Elements*.

**Whole-Cell Modelling****Evolution****Computational science****Developing biological software****Cell-to-Cell communication****Systems Biology****Learning different Mathematical formalisms****Parallel computing****Machine learning**

**XVI Autumn School and X National Meeting of Mathematical Biology.**

Scholarship holder.

UNAM Science Faculty, Juriquilla, Querétaro Campus. November 2014

**Symposium "The Major Transitions In Evolution".**

** **Attendant.

Mexico City. March 2015

**RECOMB/ISCB Conference on Regulatory and Systems Genomics, with Dream Challenges.**

Attendant.

Philadelphia, Pennsylvania. November 2015

**English**

Speak: Intermediate level.

Read/Write: high proficiency.

**Spanish**

** ** Native language.

- Play Soccer
- Play Basketball
- Reading
- Listen to music
- Walk and Explore
- Biking

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