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Clare's Home Page (archive, partial, from Bowdoin)Clare Bates Congdon Visiting Associate Professor Department of Computer Science, Bowdoin College, Brunswick, Maine |
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contact me: | email: | congdon@bowdoin.edu | |
phone: | 207.725.3824 (I check messages irregularly... email is usually the best way to reach me) | ||
sue's phone: | 207.725.3567 (Sue Theberge is the CS Department Coordinator) | ||
cs dept. fax: | 207.725.3750 | ||
us mail: | Clare Bates Congdon, Computer Science, Bowdoin College, 8650 College Station, Brunswick, ME 04011-8486 | ||
find me: | office: | 109
Banister Hall (Yes, that's the Chapel. I'm at the back
on the side by the polar bear statue) | |
lab: | 108 Banister Hall |
Spring 2018: | CSCI 1101: Intro to Computer Science |
Fall 2017: | CSCI 3665: Interactive Data Visualization |
Spring 2017: | CSCI 1101: Intro to Computer Science |
CSCI 2600: Introduction to Data Mining | |
Fall 2016: |
CSCI 1101: Intro to Computer Science
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CSCI 3665: From Data to Visualization: Designing Interactive Approaches to Understanding Information | |
CSCI 4029, Advanced Collaborative Study: Bioinformatics | |
Spring 2016: | CSCI 1101: Intro to Computer Science |
CSCI 4029, Advanced Collaborative Study: Bioinformatics | |
Fall 2015: | CSCI 3455: Machine Learning |
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GAMI: genetic algorithms for motif inference Synopsis: In this project, we develop computational tools to infer regulatory regions in noncoding DNA, based on conservation over evolutionary time, and including biochemical data from the ENCODE project. Current and recent collaborators: Leif Oxburgh, Carol Kim, Jim Coffman Current staff and students: Craig Lessard, Sam McFarland, Brenna Gardner, Naomi Heuer, Amanda Castonguay, Ben Congdon-Jones
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GPS: Genome Pattern Scan Synopsis: In this project, we develop computational tools that identify genes that might be influenced by specific regulatory factors (specified by the user). Collaborators: Leif Oxburgh, Mary Ann Asson-Batres Staff and students: Sam McFarland, Craig Lessard, Jen Fetting
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Gaphyl: genetic algorithms for phylogenetics Synopsis: Find the most plausible evolutionary relationships among species Staff and students: Emily Greenfest, Josh Ladieu, Kevin Septor, Lunn Sawyer |
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REALM: A Rule-Based Evolutionary Computation Agent that Learns to Play Mario
Synopsis: Using an evolutionary computation approach to learn to play Mario. Masters project by Slawomir Bojarski |
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RAMP: A Rule-Based Agent for Ms. PacMan Synposis: As of 2008, the best artificial agent for Ms. PacMan, with a high score of 25,520; winner of the WCCI 2008 Ms. PacMan competition Masters project by Alan Fitzgerald Contributors: Peter Kemeraitis Base code and competetion run by Simon Lucas |
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Learning to Play Unreal Synposis: Development of Chimera, an evolutionary approach to learning rule-based systems and Agent Smith, an agent to play Unreal. A hand-coded version of Agent Smith won the CEC 2009 Unreal Tournament competition. Independent study project by Ryan Small |