DePauw University
 Spring 2020
(soc: 4018)

Instructor: Fornari

BIO 325A

Lecture: 9:10-10:10 MWF
in Olin 136; Lab: 1:40-3:30 T in Olin 205

Instructor: Chet Fornari
office: Olin 232
e-mail: cfornari

click here for all registration information
click here for older Genomics Syllabus

Required Texts:
(1) Bioinformatics & Functional Genomics, 3rd edtion (Oct 26, 2015); ISBN 978-1-118-581780 (cloth, $120.00; $90.00 e-text) by Jonathan Pevsner (paperback and e-books avalilable also at lower prices)

(programming is not required for this course at this time; any programming in R, Linux command line, or Python is introduced from strictly basic concepts and practices, and applied to specific bioinformatic problems and exercises, many of which are presented very effectively in the BFG text - learn by doing*)

Strongly Recommended: (2) Phylogenetic Trees Made Easy, 5th edition by Barry Hall ($31.00 at Amazon Books) most helpful for the MEGA X suite of programs; also introduces basic concepts and practices in computer programming, databases, and network theory

(An alternative text as a resource for in-depth treatments, but NOT required: Understanding Bioinformatics)

other helpful but NOT required resources:
(1) Computer Science Illuminated; (2) Practical Computing for Biologists; (3) Building Bioinformatics Solutions with Perl, R, and MYSQL; (4) Bioinformatics for Biologists;
(5) Bioinformatics for Beginners

(6) if you have a Python background or interenst in learning it:
Computational Methods for Bioinformatics: Python 3.4 and Python for Biologists

Pre-requisites: BIO 101 or CHEM 240 or equivalent and a strong curiosity about how to transform biological data into knowledge, understanding, and discovery as part of the Biological Revolution, with special emphasis on Medical Informatics

*R.W. Hamming's famous maxim: The purpose of computing is insight, not numbers

Resources for BIO 325

Biological Databases from Wikipedia (2019 update)

What is BIO 325, Bioinformatics?

Think of it as the computational analysis - by way of specific algorithms (often embedded in more general scripts and programs with user-friendly GUIs) - of molecular sequence data to test hypotheses about modeled biological processes for understanding molecular structures, genomes and functions in order to make Discoveries.

"The great challenge in biological research today is how to turn data into knowledge.
I have met people who think data is knowledge but these people are then striving
for a means of turning knowledge into understanding."

Syndney Brenner: The Scientist 16(6): 12, March 18, 2002

"Where is the Life we have lost in living?
Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in information?"
TS Elliot, The Rock

"How often have I said to you that when you have eliminated the
impossible, whatever remains, however improbable must be the truth?"
Sherlock Holmes to his friend Dr. Watson, in The Sign of Four by
Arthur Conan Doyle, 1890, chapter 6


What is "Genomics"? on the highlighted links for the definitions...

What is "Bioinformatics"?

Our Main Theme: Computational Analysis of Sequence, Structure, Function to make Discoveries!
Our Main Goals: (1) to understand Biological systems and processes, to discover new
knowledge about Biological systems through computational analyses of molecular sequences and whole genomes, to decipher Genotype to Phenotype relationships & Emergent Properties, and (2) to understand the theoretical basis of the algorithms used in the programs for computational analyses.

Description of Course Contents

The lecture portion of the course serves two purposes (and click here for Projects and Presentations):

(1) to introduce you to the basic, core concepts of Bioinformatics, which underlie the many, many applications used by computational biologists to extract knowledge and understanding from myriads of databases. How is sequence information collected, stored and organized, managed and distributed? MOST IMPORTANTLY, how can we use sequence information to understand complex biological processes? Which bioinformatic methods best reveal and conceptualize the raw information provided by genomics and proteomics research? (See Course Outline in FlowChart format).

(2) to provide you with a solid theoretical basis for not only methodology but also more importantly for hypothesis construction and testing by proper experimental design (i.e., the scientific method used in genomics and bioinformatics)

Together we will try to get at least a glimpse of the subtle variations in relatively simple biological structures, and how these variations combine in numerous ways to contribute to a wonderful and exciting biological complexity and hence diversity. As always with all my courses, the pedagogy rests on two main themes: (1) Knowing, understanding, and analyzing major concepts, and how these concepts relate to each other, to the major concepts of all biology, and to disciplines and ideas outside the normal realm of biological science; (2) Understanding the theory and practice of the scientific method, and then how it transforms questions, observations, problems, etc., into concept and ultimately theory by way of well designed experiments coupled with informed interpretation of the experimental data.

Every attempt will be made to integrate major concepts to show the unity of the various sub-disciplines comprising molecular biology by applying the knowledge and techniques of genomics and bioinformatics. Every attempt will be made to collect a seemingly overwhelming amount of details into regular, concept-based patterns forming the over-arching themes and principles of modern biology. Yes, these patterns and themes exist! Reductionism will lead to Holism, especially by way of Bioinformatics, and to an increased awareness of how sets of regularly repeating themes and patterns, first observed in macromolecular sequences, combine in myriad ways to generate the wonderful, rich diversity of living organisms. Then you will embark on a new and exciting adventure into Systems Biology...

A note about your texts for this course: a constant, repeating theme throughout the texts, in each chapter, almost like a fractal image, (and this site too, and this one) is the fundamental relationship of structural genomics to functional genomics to comparative genomics, which is interlaced always with computational analyses.

Outline of Course Contents: Lecture Topics and Reading Assignments


Please Note: each of the following sections is divided into Reading Assignments and Web-links; the reading assignments can be found by clicking the listed links, while the Web-links and other useful information are located on the Resources for BIO 325 page

Review of the Basics: Nucleic Acid & Protein SEQUENCES

Part I: Sequence Databases and Information Retrieval

II. Pairwise Sequence Comparisons


IV. Protein Sequence and Structure Analyses

V. MSA's or Multiple Sequence Alignments

VI. Molecular Phylogenetic Analyses


Grade categories, distributions, scaling,:
OPAs, MuPAs, Labs = 50% of final grade
Project (th) = 50% of final grade

Links to Web Sites & Server Programs Used in this course

(A) Databases:

Nucleic Acids Research Journal with access to all 2020

(B) Model Organisms:

MGI 2.7 - Mouse Genome Informatics
ZFIN (Zebrafish Genome)
BDGP Home (drosophila)
FlyBase @
The Institute for Genomic Research (Microbes)
TIGR - CMR (Bacteria/Archaea)
Saccharomyces Genome Database (yeast)

(C) Genome Comparisons:

Human Genome Browser

(D) MSA's:

Clustal Omega

(E) Phylogenetics:

MEGA - Molecular Evolutionary Genetics Analysis
Bayesian Phylogeny
NJplot (plots trees in PDF format)


Links Collections for Specific Tasks in Genomics & Bioinformatics:

Systems Biology

Animal Diversity


Tree of Life

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