Teaching
Courses Developed
Computational Genomics and Genomics
Both, Computational Genomics (undergraduate level) and Genomics (graduate level), are courses designed to prepare students for the Genomics Revolution. They both provide a broad, basic understanding of the different approaches used in the acquisition and study of genome data. Students learn how to obtain, organize, manipulate, and process biological data, using local-, super- and cloud-computers. For this, we use web-interface-based computational tools like Galaxy and CyVerse, to study genome data. Both courses aim at preparing students to understand and to perform basic genome analysis, which will in turn prepare them to follow and understand the most up-to-date work performed in biology. Computational Genomics_ and Genomics make extensive use of XSEDE and Jetstream cloud computational resources. Genomics and Computational Genomics are both mature courses that have been offered since the years 2000 and 2010, respectively.
Digital Biology
Digital Biology (graduate level)is a command-line-driven introductory course, designed to prepare students for the paradigm shift in our understanding of biology that has been generated by the quick development of the fields of Genomics and Computational Genomics. This course aims at developing terminal-based skills to obtain, organize, manipulate, and process biological data, with a focus on mapping and assembly of transcriptome data. Students learn the fundamentals of version control, scripting, text manipulation, and emerging computational tools available on local computers, super computers, and in the cloud. Learning the fundamentals of Version Control (GIT), scripting (BASH), text manipulation (SED/AWK), as well as other essential Genomics tools including, but not restricted to SAM, BED and Picard, allows students to ask and answer important biologically relevant questions. This helps them design, perform and analyze experiments using Mapping and Assembling software available at Cyverse and the TAMU Supercomputer Grace. Digital Biology makes extensive use of XSEDE and Jetstream cloud computational resources. Digital Biology is a mature course that has been offered since 2012.
Advanced Eukaryotic Genetics and Epigenetics
Advanced graduate level course developed to provide a comprehensive understanding of both genetics and epigenetics topics related to RNA silencing. The course is based on the study of the use of genetic approaches to understand basic biological processes and genetic processes in both small (e.g., fungi) and large (e.g., mouse) eukaryotic organisms. In addition, we study classical examples where a non-mendelian genetic segregation is observed. In particular, we explore the exploding literature in the RNA silencing field, paying particular attention to the biology of the newly discovered non-coding RNAs. Students are exposed to the most up-to-date molecular and genetic literature in these fields. At the end of the course, students are expected to have an advanced understanding of the genetic and epigenetics of the most important eukaryotic model organisms and of the most relevant epigenetic problems.
Information In Biology
This undergraduate and graduate level course was an attempt to tackle a heavily interdisciplinary subject. It focused on identifying and understanding the laws that govern and the processes that control information transfer in Biology. Our working hypothesis is that the same laws that control information transfer in other systems (e.g., large corporations) are present in unicellular organisms like Escherichia coli and vice-versa. Our dream is to translate these concepts in the production of software or hardware with "evolvability" properties.
Courses Taught As Professor
Graduate Level
| NAME | NUMBER | YEAR(s) | CREDIT(S) |
|---|---|---|---|
| Genomics | BIOL650 | 2000 - 2023 | 03 Credits |
| Advanced Eukaryotic Genetics and Epigenetics | BIOL689 | 2003 – 2005 | 04 Credits |
| Digital Biology | BIOL647 | 2012 - 2024 | 04 Credits |
Undergraduate Level
| NAME | NUMBER | YEAR(s) | CREDIT(S) |
|---|---|---|---|
| Cellular and Molecular Biology | BIOL213 | 2023 - 2024 | 03 Credits |
| Computational Genomics | BIOL350 | 2010 - 2023 | 03 Credits |
| Fundamentals of Microbiology | MICR351 | 2004 – 2005 | 04 Credits |
| Directed Studies in Biological Thought (Darwin and The Art of War) | BIOL285 | 2002 | 01 Credits |
| Bacterial Genetics | MICR406 | 1997 – 2000 | 03 Credits |
Courses Taught As Teaching Assistant
| NAME | NUMBER | YEAR(s) | CREDIT(S) |
|---|---|---|---|
| Laboratory Course in Molecular Biology | Molecular Biology | 1985 | 02 Credits |
Undergraduate Level
| NAME | NUMBER | YEAR(s) | CREDIT(S) |
|---|---|---|---|
| Genetics | GENE301 | 1989 | 03 Credits |
| Advanced Molecular Biology | Molecular Biology II | 1984 | 03 Credits |
| Biology 101 | BIOL101 | 1978 | 03 Credits |