Hamed Abdollahi
Molecular Biologist
Genomics Postdoctoral Fellow
DVM, PhD
Computational Structural Biology
Section 001, CRN 27574
Last Updated 8/21/2024
Credit Hours: 3 Credit Hours
Instructional Method: Face-to-Face Instruction
Campus: USC Columbia
Part of Term: 30 (Columbia Full Term)
Description:
This course is intended to familiarize interested investigators with theoretical concepts and some subset
of the algorithmic tools currently utilized in the field of protein folding such as AlphaFold, ROSETTA and I-TASSER. Other software packages such as VMD and NAMD that are extensively used by the community of experimental/computational biologists will also be introduced. Upon the completion of this course, participants are expected to be able to embark in competitive research in the area of protein folding.The general outline of this course will consist of a brief introduction to main concepts of molecular biology, introduction to experimental methods of protein structure determination (mostly NMR) and, introduction to general classes of protein folding approaches (Ab Initio versus threading). Various visualization, evaluation and computation tools will be introduced along the way. The following includes some example topics:
- Topics in structural biology
- Topics in protein structure characterization and classification.
- Topics in experimental data (NOE and RDC data from NMR)
- Computational protein folding by force field minimization and constrained optimization.
- Protein folding based on threading algorithms.
- Topics in molecular modeling, molecular mechanics and quantum mechanics
Algorithms in Bioinformatics
Section 001, CRN 59207
Last Updated 8/21/2024
Credit Hours: 3 Credit Hours
Instructional Method: Face-to-Face Instruction
Campus: USC Columbia
Part of Term: 30 (Columbia Full Term)
Description:
This course aims to introduce the central concepts, algorithms and tools that define Bioinformatics and are important problems in Bioinformatics major topics including nucleotide and amino acid sequence alignment, DNA fragment assembly, phylogenetic reconstruction, and protein structure visualization and assessment.The general outline of this course will consist of a brief introduction to main Biological concepts, programming concepts, followed by delving into the core concepts in Bioinformatics. More specifically, the following topics discussed:
- Topics in Biology, Genetics, and Molecular Biology.
- Topics in introductory programming in Python.
- Topics in pairwise sequence alignment and dynamic programming
- Topics in multiple sequence alignment.
- Topics in phylogenetic analysis and visualization.
- Topics in Biopython.
- Introduction to various biological databases.
- Introduction to probabilistic Motifs, stochastic algorithms, and hidden Markov Models.