User profiles for Leelavati Narlikar

Leelavati Narlikar

Data Science, IISER Pune
Verified email at iiserpune.ac.in
Cited by 1273

[PDF][PDF] Genome-wide analyses of transcription factor GATA3-mediated gene regulation in distinct T cell types

…, R Yagi, R Jothi, K Cui, S Sharma, L Narlikar… - Immunity, 2011 - cell.com
The transcription factor GATA3 plays an essential role during T cell development and T helper
2 (Th2) cell differentiation. To understand GATA3-mediated gene regulation, we identified …

Identifying regulatory elements in eukaryotic genomes

L Narlikar, I Ovcharenko - Briefings in functional genomics and …, 2009 - academic.oup.com
Proper development and functioning of an organism depends on precise spatial and
temporal expression of all its genes. These coordinated expression-patterns are maintained …

Genome-wide discovery of human heart enhancers

L Narlikar, NJ Sakabe, AA Blanski, FE Arimura… - Genome …, 2010 - genome.cshlp.org
The various organogenic programs deployed during embryonic development rely on the
precise expression of a multitude of genes in time and space. Identifying the cis-regulatory …

[HTML][HTML] A nucleosome-guided map of transcription factor binding sites in yeast

L Narlikar, R Gordân, AJ Hartemink - PLoS computational biology, 2007 - journals.plos.org
Finding functional DNA binding sites of transcription factors (TFs) throughout the genome is
a crucial step in understanding transcriptional regulation. Unfortunately, these binding sites …

ChIP-Seq data analysis: identification of Protein–DNA binding sites with SISSRs peak-finder

L Narlikar, R Jothi - Next Generation Microarray Bioinformatics: Methods …, 2012 - Springer
Protein–DNA interactions play key roles in determining gene-expression programs during
cellular development and differentiation. Chromatin immunoprecipitation (ChIP) is the most …

Informative priors based on transcription factor structural class improve de novo motif discovery

L Narlikar, R Gordân, U Ohler, AJ Hartemink - Bioinformatics, 2006 - academic.oup.com
Motivation: An important problem in molecular biology is to identify the locations at which a
transcription factor (TF) binds to DNA, given a set of DNA sequences believed to be bound by …

[HTML][HTML] Machine learning prediction of non-attendance to postpartum glucose screening and subsequent risk of type 2 diabetes following gestational diabetes

…, V Patel, N Sukumar, R Siddharthan, L Narlikar… - Plos one, 2022 - journals.plos.org
Objective The aim of the present study was to identify the factors associated with non-attendance
of immediate postpartum glucose test using a machine learning algorithm following …

Finding regulatory DNA motifs using alignment-free evolutionary conservation information

R Gordaˆn, L Narlikar, AJ Hartemink - Nucleic Acids Research, 2010 - academic.oup.com
As an increasing number of eukaryotic genomes are being sequenced, comparative studies
aimed at detecting regulatory elements in intergenic sequences are becoming more …

One size does not fit all: on how Markov model order dictates performance of genomic sequence analyses

L Narlikar, N Mehta, S Galande… - Nucleic acids …, 2013 - academic.oup.com
The structural simplicity and ability to capture serial correlations make Markov models a
popular modeling choice in several genomic analyses, such as identification of motifs, genes …

Sequence features of DNA binding sites reveal structural class of associated transcription factor

L Narlikar, AJ Hartemink - Bioinformatics, 2006 - academic.oup.com
Motivation: A key goal in molecular biology is to understand the mechanisms by which a cell
regulates the transcription of its genes. One important aspect of this transcriptional …