Biology 202

Bioinformatics

with Dr. Lyons-Weiler

Classes Start June 1, 2021 Online, Live [REGISTRATION IS OPEN!]
Amaze and astound your friends and family! Imagine if you could analyze any DNA, RNA or protein sequence and run analyses to determine its likely identify, function, structure, and relationships to other sequences.  If it's an RNA sequence, what is its likely structure?  If it's DNA, does it encode a protein?  Does the protein have a likely special function, or cellular location?  Does the protein have conserved domains?  If it's a viral or bacterial protein, does it have any immunogenic epitopes?  If so, what are they, and do they match human proteins in a manner that might lead to pathogenic priming?  Plus much, much more...

Syllabus

Course Description: This course will provide students with an introduction to some of the important fundamental skill sets in Bioinformatics. In-depth description of methods and algorithms will provide background and hands-on experience with software will provide practical experience. Concepts and approaches to DNA and amino acid sequence alignment, homology, conserved domain identification, phylogenetic inference, array-based transcriptomics, quantitative PCR analysis and peptide identification searches will be presented. Basic computing skills are required.

Learning Outcomes:

Students will

  • Understand molecular biology of genes, transcription and translation beyond central dogma

  • Search biological databases containing sequences, clinical, and structural information

  • Retrieve information from these biological databases

  • Perform structure/function analysis of biological molecules

  • Perform DNA/protein sequence alignment and analysis

  • Identify homologs and conserved domains

  • Perform a basic phylogenetic inference from a multiple sequence alignment

  • Identify differentially expressed genes in a microarray data set

  • Be able to interpret the output of a quantitative RT-PCR experiment

  • Understand peptide identification search algorithms given proteomics profiles

  • Be able to detect structure in small RNAs

Time Tuesdays 1:00PM-3:00PM

Instructor: James Lyons-Weiler

Required Materials: Students will make extensive use of computers and the internet. PC software to be used includes various web applications.

Recommended Text(s): Recommended readings will be sent each week. The book that most closely parallels our in-class experiences is David Mount’s Bioinformatics: Sequence and Genome Analysis. However, every student of Biotechnology should get and read a copy of Campbell & Heyer’s Discovering Genomics, Proteomics and Bioinformatics.

Directed Study: Data analysis using web-based database searches, sequence analysis, protein structure analysis, phylogenetic trees, transcriptomics, proteomic peptide identification, qPCR. Interpretation of current journal articles involving bioinformatics and QA/QC.

Teaching Methods:

Emphasis on learning by doing – directed exercises in 1) use of a variety of web applications, 2) interpretation of results from those applications, 3) in-class/take-home exercises that build on past experiences, 4) in-class quizzes.

The assignments and content will rely on web-based tutorials and specific assignments from bioinformatics web-sites. The tools and resources for bioinformatics are generally free to the public. They lend themselves to exploration, so students are encouraged to ask and seek answers for impromptu questions.

Course Plan:

1 Beyond the Central Dogma Course Overview.

Lecture on transcription, translation, alternative splicing, RNA editing, post-translational modification. Find splice variants (isoforms) of sequences with the same gene name in Genbank. Homework Assignment #1

2 Overview of Bioinformatics Resources.

 General description of bioinformatics resources, introduction to NCBI, Genbank, Pubmed, Nucleotide, Protein Identify a gene of interest related to a disease or disease state of interest to the student. Find the nucleotide sequence in the Nucleotide database. Find the protein sequence in the Nucleotide entry and in the Protein database. Homework Assignment #2

3 BLAST Searching sequence databases.

Performing BLAST comparisons between two sequences. BLASTing one sequence against a chosen database In-class/take-home exercise. BLAST a sequence of interest against Nucleotide database @ NCBI and BLAST 2 Sequences. Homework Assignment #3

4 Pairwise Sequence Alignment

Principles of sequence alignment algorithm In-class/take-home exercise with alignment of two sequences. Homework Assignment #4

5 Studying Your Sequence Open Reading Frames and the Conserved Domain Database In-class/take-home exercise of finding open reading frames in nucleotide sequences using ORF, and finding conserved domains in protein sequences via the CDD. Homework Assignment #5

6 Identifying Immunogenic Epitopes in Pathogen Proteins

7 Identifying Potentially Autoreactogenic Epitopes in Pathogen Proteins

8 Conserved Domains Conserved Domain Database part 2 and Homologene

In-class/take-home exercise on identification of conserved domains in amino acid coding sequences and finding homologs. Homework Assignment #6

9 Phylogenetic Inference ClustalW multiple sequence alignment tools.

Tools for estimating phylogenetic trees. Derive a multiple alignment and a phylogenetic tree for homologs of the student’s sequence of interest.

Homework Assignment #7

 10 Transcriptomics with Microarrays 1 The Basics Read an overview on transcriptomics with microarrays. None.

11 Transcriptomics with Microarrays 2

 Normalization/Transformation; Identifying Differentially Expressed Genes Implement a simple analysis comparing gene expression in two clinical groups using a web application. Homework Assignment #8

12 Quantitative

PCR Interpretation of qRT-PCR results Given qRT-PCR output, perform interpretation of CT values. Homework Assignment #9

13 Proteomics:

Peptide identification Mass-spec profile peptide identification/

Mascot/Sequest/X-Tandem/Consensus Perform an online peptide fingerprint search Homework Assignment #10

14 Small RNAs

 Computational Analysis of Small RNAs Use web tools to predict small RNA structure/function Homework Assignment #11

15 Summing it All Up