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Ibrahim Numanagić
Researcher at Massachusetts Institute of Technology
Publications - 33
Citations - 670
Ibrahim Numanagić is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Genotyping & Medicine. The author has an hindex of 10, co-authored 22 publications receiving 469 citations. Previous affiliations of Ibrahim Numanagić include Simon Fraser University & Indiana University.
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SCALCE: boosting sequence compression algorithms using locally consistent encoding
TL;DR: SCALCE, a 'boosting' scheme based on Locally Consistent Parsing technique, which reorganizes the reads in a way that results in a higher compression speed and compression rate, independent of the compression algorithm in use and without using a reference genome is presented.
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Comparison of high-throughput sequencing data compression tools.
Ibrahim Numanagić,James K. Bonfield,Faraz Hach,Faraz Hach,Jan Voges,Jörn Ostermann,Claudio Alberti,Marco Mattavelli,S. Cenk Sahinalp,S. Cenk Sahinalp,S. Cenk Sahinalp +10 more
TL;DR: A benchmarking study of available compression methods on a comprehensive set of HTS data using an automated framework to report on the development of compression methods for high-throughput sequencing data size reduction.
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Allelic decomposition and exact genotyping of highly polymorphic and structurally variant genes.
Ibrahim Numanagić,Ibrahim Numanagić,Salem Malikic,Michael J. Ford,Xiang Qin,Lorraine Toji,Milan Radovich,Todd C. Skaar,Victoria M. Pratt,Bonnie Berger,Stephen W. Scherer,S. Cenk Sahinalp +11 more
TL;DR: A combinatorial optimization framework is introduced that successfully resolves this challenging problem of allelic decomposition of highly polymorphic, multi-copy genes through using whole or targeted genome sequencing data and an associated computational tool Aldy is developed.
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Fast characterization of segmental duplications in genome assemblies
Ibrahim Numanagić,Alim S Gökkaya,Lillian Zhang,Bonnie Berger,Can Alkan,Faraz Hach,Faraz Hach +6 more
TL;DR: SEgmental Duplication Evaluation Framework (SEDEF) is introduced to rapidly detect SDs through sophisticated filtering strategies based on Jaccard similarity and local chaining and captures up to 25% ‘pairwise error’ between segments, allowing us to more deeply track the evolutionary history of the genome.
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DeeZ: reference-based compression by local assembly
Faraz Hach,Faraz Hach,Ibrahim Numanagić,Ibrahim Numanagić,S. Cenk Sahinalp,S. Cenk Sahinalp,S. Cenk Sahinalp +6 more
TL;DR: It is proposed that obtaining an initial image to map astrocyte locations (within ~45 min after dye application) in addition to performing detailed morphological analysis of single cells allows them to be distinguished from oligodendrocytes.