TITLE: 

Computational Proteomics: 
Genome-scale Analysis of Protein Structure, Function, & Evolution

Mark Gerstein

P Harrison, J Qian, R Jansen, V Alexandrov, P Bertone, R Das, 
D Greenbaum, W Krebs, Y Liu, H Hegyi, N Echols, J Lin, C Wilson, 
A Drawid, Z Zhang, Y Kluger, N Lan, N Luscombe, S Balasubramanian

Molecular Biophysics & Biochemistry Department
Yale University
New Haven, CT 

http://bioinfo.mbb.yale.edu

My talk will address two major post-genomic challenges: trying to
predict protein function on a genomic scale and interpreting
intergenic regions. I will approach both of these through analyzing
the properties and attributes of proteins in a database framework. The
work on predicting protein function will discuss the strengths and
limitations of a number of approaches: (i) using sequence similarity;
(ii) using structural similarity; (iii) clustering microarray
experiments; and (iv) data integration. The last approach involves
systematically combining information from the other three and holds
the most promise for the future. For the sequence analysis, I will
present a similarity threshold above which functional annotation can
be transferred, and for the microarray analysis, I will present a new
method of clustering expression timecourses that finds "time-shifted"
relationships.  In the second part of the talk, I will survey the
occurrence of pseudogenes in several large eukaryotic genomes,
concentrating on grouping them into families and functional categories
and comparing these groupings with those of existing "living" genes.
In particular, we have found that duplicated pseudogenes tend to have
a very different distribution than one would expect if they were
randomly derived from the population of genes in the genome.  They
tend to lie on the end of chromosomes, have an intermediate
composition between that of genes and intergenic DNA, and, most
importantly, have environmental-response functions. This suggests that
they may be resurrectable protein parts, and there is a potential
mechanism for this in yeast.


References

J Qian, B Stenger, C Wilson, J Lin, R Jansen, W Krebs, V Alexandrov, 
     N Echols, S Teichmann, J Park, M Gerstein. 
     "PartsList: a web-based system for dynamically ranking protein folds 
     based on disparate attributes, including whole-genome expression 
     and interaction information." 
     Nucleic Acids Res 29: 1750-64 (2001).

P Harrison H Hegyi, P Bertone, N Echols, T Johnson, S Balasubramanian, 
     N Luscombe, M Gerstein.  
     "Digging for dead genes: an analysis of the characteristics of 
     the pseudogene population in the Caenorhabditis elegans genome." 
     Nucleic Acids Res 29: 818-30 (2001).

J Qian, M Dolled-Filhart, J Lin, H Yu, M Gerstein.
     "Beyond synexpression relationships: Local Clustering of time-shifted and 
     inverted gene expression profiles identifies new, biologically relevant interactions."
     J Mol Biol 314: 1053-1066 (2001). 

R Jansen, D Greenbaum, M Gerstein.
     "Relating whole-genome expression data with protein-protein interactions."
      Genome Research 12: 37-46 (2002). 

P Harrison, H Hegyi, P Bertone, N Echols, T Johnson, S Balasubramanian, 
     N Luscombe, M Gerstein.
     "Molecular fossils in the human genome: 
     Identification and analysis of pseudogenes in chromosomes 21 and 22."
     Genome Research 12: 273-281 (2002).