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Contact details
- Email: ihh
 berkeley  edu
- Skype: ianholmes
- AIM/iChat: dartcoder@mac.com
- Fax2email: (866) 486 - 7316
- Lab address: 381 Stanley Hall, UC Berkeley, CA 94720-3220
- Lab phone: (510) 643 - 3793
Affiliations
I am on the faculty of the Department of Bioengineering in UC Berkeley
and the Physical Biosciences Division at Lawrence Berkeley Laboratory.
I'm affiliated with the following UC Berkeley/UCSF Graduate Groups:
Biographical info
I grew up in Cambridge (UK) and studied physics at the Cavendish Laboratory (TCM group) and genomics at the Sanger Institute (Informatics).
I now work at UC Berkeley and live in East Oakland.
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Lorne, December 2006
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Links
Some pages on this site that I maintain:
I also keep a teaching blog, named Genome Dynamics.
Other reasonably fresh links:
Research interests
I am interested in computational biology, and in particular, in building realistic, predictive, quantitative models of the evolution of genomes and biological systems.
By "realistic, quantitative models" I mean stochastic process models---typically discrete-state continuous-time Markov chains---that incorporate not just the "easy" effects (point substitution)
but increasingly complex effects too (indels, context-sensitivity, microsatellites, local duplications & inversions, transpositions, recombination, rearrangements, gene family expansions, evolution of cis-regulation, etc.)
The goals of these endeavors are several.
There is the basic scientific challenge of wanting to have a more precise statistical theory of molecular evolutionary processes.
But we are also strongly focussed on concrete applications of the theory.
These applications span genome annotation, molecular phylogenetics, synthetic biology, in vitro evolution, serotype analysis, pathogen bioinformatics and more.
In my opinion, a well-rounded theory of genome evolution should yield the following "trifecta":
(i) measurement of evolutionary parameters (such as substitution & indel rates),
(ii) simulation of sequence evolution using a given set of parameters and
(iii) reverse Bayesian inference of evolutionary histories given observed sequence data.
Anyone who claims to be able to do one but not all of these things (e.g. simulating evolution without measuring the relevant evolutionary rates from experimentally-obtained sequence data)
does not really have a theory of evolution.
A related interest is "genome ecology": the (evolutionary) interactions of genomes with their neighbors.
Examples include the bioinformatics of transposon classification and the metagenomics of microbial communities.
Here are some specific interests (with links to other pages on this site where you can find more details):
- Using bioinformatics to investigate genomes, their evolution and ecology;
- Developing new software for genomics (from Web 2.0/AJAX to molecular evolution);
- Developing, analyzing and applying probabilistic models for sequence analysis. Examples:
- Computational methods for synthetic biology, such as design tools for RNA engineering.
For more info see the front page, the Holmes lab page or the paper archive.
Notes to self
Self indulgence
Apropos of not much, here are my favorite retro computer games of all time:
I did write a couple of games myself as a kid:
Miscellany
- A 77x123 thumbnail from a picture of me in Kew on January 21st, 2007.
- Here's the thumbnail of the thumbnail:
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Alameda, March 2007
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Essentially it was a fast four-way scrolling arcade/puzzle/RPG with a level designer. There's a review 
