Introduction to Bioinformatics and Computational Biology for Biomedical Research, Lecture notes of Evolutionary biology

Download Introduction to Bioinformatics and Computational Biology for Biomedical Research and more Lecture notes Evolutionary biology in PDF only on Docsity! Genomics & Comp. Biology (GCB)           1 GENOMICS & COMP. BIOLOGY (GCB) GCB 4930 Epigenetics of Human Health and Disease Epigenetic alterations encompass heritable, non-genetic changes to chromatin (the polymer of DNA plus histone proteins) that influence cellular and organismal processes. This course will examine epigenetic mechanisms in directing development from the earliest stages of growth, and in maintaining normal cellular homeostasis during life. We will also explore how diverse epigenetic processes are at the heart of numerous human disease states. We will review topics ranging from an historical perspective of the discovery of epigenetic mechanisms to the use of modern technology and drug development to target epigenetic mechanisms to increase healthy lifespan and combat human disease. The course will involve a combination of didactic lectures, primary scientific literature and research lectures, and student-led presentations. Spring, even numbered years only Also Offered As: BIOL 4244, CAMB 4930 Prerequisite: BIOL 2210 1 Course Unit GCB 5330 Statistics for Genomics and Biomedical Informatics BMIN 5330 is an introductory course in probability theory and statistical inference for graduate students in Genomics and Computational Biology. The goal of the course is to provide foundation of basic concepts and tools as well as hands-on practice in their application to problems in genomics. At the completion of the course, students should have an intuitive understanding of basic probability and statistical inference and be prepared to select and execute appropriate statistical approaches in their future research. Also Offered As: BMIN 5330, IMUN 5770 1 Course Unit GCB 5340 Experimental Genome Science This course will survey methods and questions in experimental genomics, including next generation sequencing methods, genomic sequencing in humans and model organisms, functional genomics, proteomics, and applications of genomics methods. Students will be expected to review and discuss current literature and to propose new experiments based on material learned in the course. Prerequisite: Undergraduates and Masters students need BIOL 431. Also Offered As: PHRM 5340 Prerequisite: BIOL 4231 1 Course Unit GCB 5350 Introduction to Bioinformatics This course provides overview of bioinformatics and computational biology as applied to biomedical research. A primary objective of the course is to enable students to integrate modern bioinformatics tools into their research activities. Course material is aimed to address biological questions using computational approaches and the analysis of data. A basic primer in programming and operating in a UNIX enviroment will be presented, and students will also be introduced to Python R, and tools for reproducible research. This course emphasizes direct, hands-on experience with applications to current biological research problems. Areas include DNA sequence alignment, genetic variation and analysis, motif discovery, study design for high-throughput sequencing RNA, and gene expression, single gene and whole-genome analysis, machine learning, and topics in systems biology. The relevant principles underlying methods used for analysis in these areas will be introduced and discussed at a level appropriate for biologists without a background in computer science. The course is not intended for computer science students who want to learn about biologically motivated algorithmic problems; BIOL 4536/BIOL 5536 and BE 5370/CIS 5370/MPHY 6090 are more appropriate. Prerequisites: An advanced undergraduate course such as BIOL 4210 or a graduate course in biology such as BIOL 5210, BIOL 5240, or equivalent, is a prerequisite. Fall Also Offered As: CIS 5350, MTR 5350 Prerequisite: BIOL 4210 OR BIOL 5210 OR BIOL 5240 1 Course Unit GCB 5360 Fundamentals of Computational Biology Introductory computational biology course designed for both biology students and computer science, engineering students. The course will cover fundamentals of algorithms, statistics, and mathematics as applied to biological problems. In particular, emphasis will be given to biological problem modeling and understanding the algorithms and mathematical procedures at the "pencil and paper" level. That is, practical implementation of the algorithms is not taught but principles of the algorithms are covered using small sized examples. Topics to be covered are: genome annotation and string algorithms, pattern search and statistical learning, molecular evolution and phylogenetics, functional genomics and systems level analysis. Fall Also Offered As: BIOL 5536, CIS 5360 Prerequisite: ((BIOL 1101 AND BIOL 1102) OR BIOL 1121) AND STAT 111 AND STAT 112 1 Course Unit GCB 5670 Mathematical Computation Methods for Modeling Biological Systems This course will cover topics in systems biology at the molecular/cellular scale. The emphasis will be on quantitative aspects of molecular biology, with possible subjects including probabilistic aspects of DNA replication, transcription, translation, as well as gene regulatory networks and signaling. The class will involve analyzing and simulating models of biological behavior using MATLAB. Prereqisite: Graduate standing or permission of the instructor. Fall or Spring Also Offered As: AMCS 5670, BE 5670 1 Course Unit 2022-23 Catalog | Generated 12/01/22