Fall 2008

Prerequisites: Admission to graduate standing in Bioinformatics. Students in this course will learn how to use object-oriented programming to solve common problems in bioinformatics. Topics covered will include creation and manipulation of relational databases and interfacing with standard bioinformatics programs such as CLUSTAL, BLAST and HMMer. Emphasis will be placed on the creation of memory and time efficient algorithms to handle the large data sets of post-genomic biology

This course surveys the application and interpretation of high-throughput molecular biology and analytical biochemistry methods used to produce the kinds of high-volume biological data most commonly encountered by bioinformaticians. The relationship between significant biological questions, modern biotechnology methods, and the bioinformatics solutions that enable interpretation of complex data is emphasized. Topics include: Genome sequencing and assembly, genome annotation, genome comparison. Genome evolution. Function prediction and gene ontologies. Microarray assay design, data acquisition, data analysis. Proteomics and methods and data analysis. Methods for identification of molecular interactions. Metabolic databases, pathways and models.

Departmental seminar. Weekly seminars will be given by bioinformatics researchers from within UNC Charlotte and across the world.

BINF 6010/ITSC8010 Genomics Lab

Genomics technologies are usually understood to be combinations of molecular biology methods and high-throughput platforms that generate many datasets in parallel. This has necessitated the introduction of laboratory management systems and analysis software early in the data generation process. The most mature of these technologies are, of course, DNA sequencing and fragment generation, and RNA transcript profiling methods. Students will learn to purify nucleic acids and perform quality control steps and downstream manipulations leading to sequence, fragment and transcript quantification data, on platforms used to generate genomics datasets.

A.    Course Description
Lecture: In the lecture we will cover four general topic areas: DNA-based, RNA-based, protein-based, and in vivo expression of products, directed by bio-molecular technologies. We will cover the concepts and application areas of the methods for the manipulation of the designated class of biomolecules, the instrumentation used to manipulate/purify the products and by-products, the laboratory methods used to produce the transformations leading to commercial products, and bioinformatics tools used throughout in processing and analyzing data for quality assurance and validation.
Lab: The unifying concept for the labs will be molecular diagnostics based on nucleic acids. We will purify DNA and mRNA from human cells. From the DNA fraction we will use PCR to amplify specific regions of the nuclear and mitochondrial genomes, perform fingerprint analysis of microsatellites, and perform sequencing of hypervariable regions of the mitochondrion, then do the analysis and database comparisons for identification and mutational analysis of the cells. We will do RT-PCR for a specific gene, one method for quantifying expression. We will do a microarray experiment with a small subset of labeled targets to learn how to hybridize and scan an array.

The course meets in Bioinformatics on Tuesdays and Thursdays from 11-12:15pm. The lab section meets in Cameron 217 on Tuesdays from 12:30-3pm. BINF 6010 is for MSc students and ITSC 8010 is for PhD students. No previous molecular biology lab experience is required. 

B.    Pre- or Co-Requisites

Pre-requisite: Admission to graduate standing and undergraduate training in Computer Science or one of the Life Sciences, and permission of instructor. It is assumed that students have a background that includes some molecular biology and biochemistry such that the basic types and relationships of the molecular components of cells are understood. For example, you should know what enzymes are, how they function and what their purpose is in an applied lab protocol; similarly you should know what DNA is, and what the levels of information are (sequence and gene) as well as something about the physical structure and the importance of DNA to a cell.
C.    Objectives of the Course
This course is a Research Methods course, in which students learn to purify and manipulate nucleic acids, including methods for assessing quality and yield from various sample types.
This course has two primary goals:
       1)    Students will learn the methods by which samples are manipulated in order to generate the data that is consumed in bioinformatics and computational biology experiments, and how techniques bias the end results.
       2)    Students will learn about software that is designed to assist bench scientists in quality assessment as samples are progressively manipulated in the lab.

Prerequisite: BINF 6100 or equivalent. Introduction to bioinformatics methods that apply to molecular sequence. Intro to biological databases online. Sequence databases, molecular sequence data formats, sequence data preparation and database submission. Local and global sequence alignment, multiple alignment, alignment scoring and alignment algorithms for protein and nucleic acids, genefinding and feature finding in sequence, models of molecular evolution, phylogenetic analysis, comparative modeling.

Provides a foundation in molecular genetics and cell biology focusing on foundation topics for graduate training in bioinformatics and genomics.

The aim of this 3-credit course is to introduce students to statistical methods used in further more technical courses. Basic relevant concepts from probability, stochastic processes, information theory, statistitics and experimental design will be introduced and illustrated by examples from molecular biology, genomics and population genetics with an outline of algorithms and software. R is introduced as the programming language for homework.

This course will cover: (a) overview of mechanical force fields; (b) energy minimization; (c) dynamics simulations (molecular and coarse-grained); (d) Monte-Carlo methods; (e) systematic conformational analysis (grid searches); (f) classical representations of electrostatics (Poisson-Boltzmann, Generalized Born and Colombic); (g) free energy decomposition schemes; and (h) hybrid quantum/classical (QM/MM) methods.

Project chosen and completed under the guidance of an industry partner, which results in an acceptable technical report