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Ahsan Huda

dblp:10/8712 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › epigenomics
ChIP-seq analysis
0.112010
A Gibbs sampling strategy applied to the mapping of ambiguous short-sequence tags · Bioinform. 2010
Bioinformatics and computational biology
genomics
0.112010
A Gibbs sampling strategy applied to the mapping of ambiguous short-sequence tags · Bioinform. 2010
Bioinformatics and computational biology
gibbs sampling
0.112010
A Gibbs sampling strategy applied to the mapping of ambiguous short-sequence tags · Bioinform. 2010

Methods — techniques the papers use, named apart from their topics

gibbs sampling · 0.1
YearPublicationVenuePosition
2020 Applying phenotypes to operationalize high-yield clinical features derived from a heuristic artificial intelligence model for a rare disease in the EHR
Kim Nolen, Marianna Bruno, Joshua Mitchell, Thomas George Kannampallil, Casey Reed, Mohammad Ateya, Sherry Lassa-Claxton, Michelle Holtman, Ahsan Huda
AMIA9
2010 A Gibbs sampling strategy applied to the mapping of ambiguous short-sequence tags
abstract
MOTIVATION: Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is widely used in biological research. ChIP-seq experiments yield many ambiguous tags that can be mapped with equal probability to multiple genomic sites. Such ambiguous tags are typically eliminated from consideration resulting in a potential loss of important biological information. RESULTS: We have developed a Gibbs sampling-based algorithm for the genomic mapping of ambiguous sequence tags. Our algorithm relies on the local genomic tag context to guide the mapping of ambiguous tags. The Gibbs sampling procedure we use simultaneously maps ambiguous tags and updates the probabilities used to infer correct tag map positions. We show that our algorithm is able to correctly map more ambiguous tags than existing mapping methods. Our approach is also able to uncover mapped genomic sites from highly repetitive sequences that can not be detected based on unique tags alone, including transposable elements, segmental duplications and peri-centromeric regions. This mapping approach should prove to be useful for increasing biological knowledge on the too often neglected repetitive genomic regions. AVAILABILITY: http://esbg.gatech.edu/jordan/software/map CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Jianrong Wang, Ahsan Huda, Victoria V. Lunyak, I. King Jordan
Bioinform.2