@article {43321,
	title = {ChIP-Seq data analysis: identification of protein-DNA binding sites with SISSRs peak-finder},
	journal = {Methods in molecular biology},
	volume = {802},
	year = {2012},
	month = {JAN},
	pages = {305-22},
	abstract = {Protein-DNA interactions play key roles in determining gene-expression programs during cellular development and differentiation. Chromatin immunoprecipitation (ChIP) is the most widely used assay for probing such interactions. With recent advances in sequencing technology, ChIP-Seq, an approach that combines ChIP and next-generation parallel sequencing is fast becoming the method of choice for mapping protein-DNA interactions on a genome-wide scale. Here, we briefly review the ChIP-Seq approach for mapping protein-DNA interactions and describe the use of the SISSRs peak-finder, a software tool for precise identification of protein-DNA binding sites from sequencing data generated using ChIP-Seq.},
	doi = {10.1007/978-1-61779-400-1_20},
	author = {Narlikar, Leelavati and Jothi, Raja}
}
@article { ISI:000300490500018,
	title = {Clare: cracking the language of regulatory elements},
	journal = {Bioinformatics},
	volume = {28},
	number = {4},
	year = {2012},
	month = {FEB},
	pages = {581-583},
	publisher = {OXFORD UNIV PRESS},
	address = {GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND},
	abstract = {<p>CLARE is a computational method designed to reveal sequence encryption of tissue- specific regulatory elements. Starting with a set of regulatory elements known to be active in a particular tissue/process, it learns the sequence code of the input set and builds a predictive model from features specific to those elements. The resulting model can then be applied to user-supplied genomic regions to identify novel candidate regulatory elements. CLARE{\textquoteright}s model also provides a detailed analysis of transcription factors that most likely bind to the elements, making it an invaluable tool for understanding mechanisms of tissue- specific gene regulation.</p>},
	issn = {1367-4803},
	doi = {10.1093/bioinformatics/btr704},
	author = {Taher, Leila and Narlikar, Leelavati and Ovcharenko, Ivan}
}
