1. Algorithms in Computational Biology
Tanya Berger-Wolf
Compbio.cs.uic.edu/~tanya/teaching/CompBio
January 17, 2017

2. 1D, 2D, 3D representation of DNA

3. The Central Dogma of Molecular Biology
DNA -> RNA -> Protein

4. The Central Dogma of Molecular Biology
DNA-RNA-Protein [photo credit (three slides): Bis2A (

5. The Central Dogma of Molecular Biology
(1) This happens in the cell nucleus, (2) not every letter is transcribed, (3) some are promoter regions involved in regulation of transcription and DNA replicaiton (4) some are “introns,” or untranslated regions of DNA, transcribed to RNA, but then spliced out before translation, (5) others are called “junk DNA” for their apparent lack of understood function, some are retroviral DNA, and some may really do little but space other DNA stretches, or ... possibly nothing.

6. The Central Dogma of Molecular Biology
Process of translation. mRNA (messenger RNA) is processed by a ribosome and uses tRNA (transfer RNA).

7. The Central Dogma of Molecular Biology
4^3 = 64 possible nucleotide triplet arrangements; result in 20 amino acids.
More or less universal! Some organisms have minor departures—which triplet encodes a particular amino acid.

8. The Central Dogma of Molecular Biology

9. DNA Sequencing

12. What is Computational Biology?
No standard definition!
Our definition: computational techniques for biological problems
Data acquisition, management and representation (bioinformatics)
Pattern analysis and data mining (bioinformatics)
Data analysis and optimization
Using bio data to solve other problems (medicine, public policy, etc.)
Computational biology touches all parts of computer science
Databases
Data streaming
HPC and systems
Networking
Algorithms
Privacy and security
Image processing
Visualization

13. Why is CompBio Important?
Biology perspective
More and more biological information is available => need for effectively accessing and using the information
As more detailed information is available different questions can be asked (models of evolution) => requires new math
Computer science perspective
Excellent application domain
Poses special computational challenges
Brings computer science closer to scientific discovery
Currently growing …

14. CompBio and Other Fields
Computer Science
Biology
Information
Management
Biochemistry
Molecular
Biology
Bioinformatics/ CompBio
Theoretical CS
Machine Learning
Data Mining
Biophysics
Numerical
Computing
Applied Mathematics & Statistics

15. CompBio and Bioinformatics
From Chris Burge’s MIT Open Courseware
7.91/20.490/6.874/HST.506

17. 1980s: Sequence Alignment/Search
Which specific residues/positions in a pair of proteins are homologous?
Smith-Waterman alignment algorithm
What RNA secondary structure has minimum folding free energy?
Nussinov algorithm
Zuker algorithm
How to rapidly and reliably find homologs to a query sequence in a sequence database?
FastA and BLAST algorithms and associated statistics
Temple F. Smith and Michael S. Waterman Copyright Michael Waterman
Ruth Nussinov
Michael Zuker

18. Al Gore Learns to Search PubMed
NCBI Director David Lipman (far left) coaches Vice President Gore (seated) as he searches PubMed. NIH Director Harold Varmus (center) and NLM Director Donald Lindberg (far right) look on. June 26, Photograph by the National Center for Biotechnology Information; in the public domain.

19. 1990s: HMMs, Ab Initio Protein Structure Prediction, Genomics, Comparative Genomics
How to identify domains in a protein? How to identify genes in a genome? Hidden Markov Models as a framework for such problems How to study gene expression globally, infer gene function from expression? Microarrays and clustering How to predict protein function by comparing genomes? gene fusions, phylogenetic profiling, etc. How to predict protein structure directly from primary sequence? Rosetta algorithm

20. 2000s Part 1: The human genome is sequenced, assembled, annotated genomics becomes fashionable
Criag Venter, public domain image
Photo of the Human Genome project pioneers
© Mayo Foundation for Medical Education and Research. All rights reserved.
Ewan Birney, public domain image
Jim Kent, public domain image

21. 2000s Part 2: Biological Experiments Become High-Throughput, Computational Biology Becomes more Biological Courtesy of Marc Vidal. Used with permission.
Massively parallel data collection – transcriptomics, proteomics, interactomics, metagenomics Using sequence and array data to address fundamental questions about transcription, splicing, microRNAs, translation, epigenetics, protein structure/function, development, evolution, disease, etc. Integrated computational/experimental approaches Rise of bioimage informatics
Courtesy of Marc Vidal.
Courtesy of Donald G. Moerman and Benjamin D. Williams. License: CC-BY. Source: Moerman, D. G. and Williams, B. D. "Sarcomere Assembly in C. Elegans Muscle" (January 16, 2006), WormBook, ed. The C. elegans Research Community, WormBook.

22. Topics in Bioinformatics
Genomics
Proteomics
Transcriptomics
Text Mining
Biology Literature … …
…In this paper, we report the discovery of a new gene that affects DNA reproduction in …
Gene expression & regulation
Genes
Proteins (Function)
DNA Sequences
Microarray data
Protein Sequences
AATTCATGAAAATCGTATACTGGTCTGGTACCGGC
TGAGAAAATGGCAGAGCTCATCGCTAAAGGTA
TCTGGTAAAGACGTCAACACCATCAACGTGTC
ACATCGATGAACTGCTGAACGAAGATATCCTG
TTGCTCTGCCATGGGCGATGAAGTTCTCGAGG
MKIVYWSGTGNTEKMAELIAKGIIESGKDV
DELLNEDILILGCSAMGDEVLEESEFEPFIE
KVALFGSYGWGDGKWMRDFEERMNGYG
PDEAEQDCIEFGKKIANI