@article {352,
	title = {Intensification: A Resource for Amplifying Population-Genetic Signals with Protein Repeats.},
	journal = {J Mol Biol},
	volume = {429},
	year = {2017},
	month = {2017 02 03},
	pages = {435-445},
	abstract = {<p>Large-scale genome sequencing holds great promise for the interpretation of protein structures through the discovery of many, rare functional variants in the human population. However, because protein-coding regions are under high selective constraints, these variants occur at low frequencies, such that there is often insufficient statistics for downstream calculations. To address this problem, we develop the Intensification approach, which uses the modular structure of repeat protein domains to amplify signals of selection from population genetics and traditional interspecies conservation. In particular, we are able to aggregate variants at the codon level to identify important positions in repeat domains that show strong conservation signals. This allows us to compare conservation over different evolutionary timescales. It also enables us to visualize population-genetic measures on protein structures. We make available the Intensification results as an online resource (http://intensification.gersteinlab.org) and illustrate the approach through a case study on the tetratricopeptide repeat.</p>},
	keywords = {Amino Acid Sequence, Chromosome Mapping, Codon, Computational Biology, Databases, Genetic, Evolution, Molecular, Genetics, Population, Humans, Internet, Molecular Structure, Protein Conformation, Proteins, Signal Processing, Computer-Assisted, X-Rays},
	issn = {1089-8638},
	doi = {10.1016/j.jmb.2016.12.003},
	author = {Chen, Jieming and Wang, Bo and Regan, Lynne and Gerstein, Mark}
}
@article {68,
	title = {Identifying Allosteric Hotspots with Dynamics: Application to Inter- and Intra-species Conservation.},
	journal = {Structure},
	volume = {24},
	year = {2016},
	month = {2016 05 03},
	pages = {826-837},
	abstract = {<p>The rapidly growing volume of data being produced by next-generation sequencing initiatives is enabling more in-depth analyses of conservation than previously possible. Deep sequencing is uncovering disease loci and regions under selective constraint, despite the fact that intuitive biophysical reasons for such constraint are sometimes absent. Allostery may often provide the missing explanatory link. We use models of protein conformational change to identify allosteric residues by finding essential surface pockets and information-flow bottlenecks, and we develop a software tool that enables users to perform this analysis on their own proteins of interest. Though fundamentally 3D-structural in nature, our analysis is computationally fast, thereby allowing us to run it across the PDB and to evaluate general properties of predicted allosteric residues. We find that these tend to be conserved over diverse evolutionary time scales. Finally, we highlight examples of allosteric residues that help explain poorly understood disease-associated variants.</p>},
	keywords = {Allosteric Site, Animals, Conserved Sequence, Humans, Proteome, Sequence Analysis, Protein, Software},
	issn = {1878-4186},
	doi = {10.1016/j.str.2016.03.008},
	author = {Clarke, Declan and Sethi, Anurag and Li, Shantao and Kumar, Sushant and Chang, Richard W F and Chen, Jieming and Gerstein, Mark}
}
