Next Semester Classes

Planning

Previous bioinformatics class They can give you an idea about the difficulty

level and interestingness factor

Fall: 2010Course Number Course Instructor281 Architecture Adjunct332 Algorithms Rosulek344 Operating Systems Raiford415 Computers, Ethics, Society Reimer441 Advanced Programming: Theory and Practice I Chen457 Artificial Intelligence Wright458 Bioinformatics Raiford495 Crypto Rosulek565 Advanced Database Chen595 Advanced Algorithms Rosulek

Bioinformatics Introduced to Bioinformatics Learn Perl Write the code for

A hierarchical clustering algorithm

A recursive genetic alignment algorithm

Get a gentle introduction to Hidden Markov Models Implement in Matlab

Get a gentle introduction to Principal Components Analysis Use in Matlab to analyze

multidimensional data

Bioinformatics Introduction to molecular

biology and the central dogma. Current technologies used in

sequencing genomes Introduction to Perl, using Perl

in sequence handling. How to search for similar

sequences in large sequence databases, and why such searches are so important in biological and medical research.

Phylogeny: what it is and why is it important

Prediction of RNA and protein secondary structure

Protein analysis and structure prediction

Forensic DNA analysis

CS 495/595: Cryptography [Info] What is crypto? Leveraging computation to…

… make things easy for the good guys … make things nearly impossible for the bad guys

Instructor: Mike Rosulek Prereqs:

Math 225 or 305 CS 332 recommended Programming fluency

Homeworks: Mixture of math, implementation, problem-solving, computation/number-crunching

CS 495/595: Cryptography [Topics]

Breaking “classical” ciphers: Caesar, Vigenère, newspaper “cryptogram”

Theory of classical encryption: Why one-time pads are necessary

“Modern” block ciphers (AES, DES) How to design good ones, how to break bad ones

The public-key revolution (RSA, Diffie-Hellman)

Crypto from hard problems in number theory Beyond encryption: A look into the future!

Other Courses Artificial Intelligence: Classic problems and

approaches Crypto: computational complexity used to

confound would be evesdroppers Advanced Database: Normal forms, relational

algebra, maybe some data mining Advanced Algorithms: Algorithm design, …

Complexity theory: NP-hard and NP-complete problems. Approximation algorithms for intractable problems

Finals: need to make a decision

Meeting time during semester

Final Exam Time Day

12:10 8:00-10:00 Wednesday, May 12

1:10 1:10-3:10 Monday, May 10

Go to registrar’s site: http://www.umt.edu/registrar/ Click on “students” (right below registrar’s office

banner) Click on finals week schedule. Since we meet at 12:40 have a choice between