Bin Ma mainly focuses on Computational biology, Genetics, Genome, Combinatorics and Algorithm. As a member of one scientific family, he mostly works in the field of Computational biology, focusing on Homology and, on occasion, Sequence homology and Chromosome. Bin Ma mostly deals with Genomics in his studies of Genome.
His work in Combinatorics addresses issues such as Closest string, which are connected to fields such as Longest common substring problem, Approximate string matching and Longest repeated substring problem. The concepts of his Algorithm study are interwoven with issues in String-to-string correction problem and Nearest neighbor search. His study in Reference genome is interdisciplinary in nature, drawing from both Genome evolution, Synteny, Human genome and Comparative genomics.
His primary areas of study are Combinatorics, Computational biology, Algorithm, Tandem mass spectrometry and Closest string. Bin Ma interconnects Discrete mathematics and Substring in the investigation of issues within Combinatorics. His studies deal with areas such as Genetics, Bioinformatics, De novo sequencing, Genome and Homology as well as Computational biology.
His Genome study focuses on Genomics in particular. His Algorithm research incorporates elements of Sequence, Nearest neighbor search and Mathematical optimization. His Tandem mass spectrometry study combines topics from a wide range of disciplines, such as Sequence, Peptide sequence and Glycan.
The scientist’s investigation covers issues in Mass spectrometry, Computational biology, Tandem mass spectrometry, Artificial intelligence and Pattern recognition. In general Mass spectrometry, his work in Ms ms spectra is often linked to Database search engine, Peptide and Chymotrypsin linking many areas of study. Bin Ma has included themes like Biotechnology and Genome, Bacterial genome size in his Computational biology study.
His Tandem mass spectrometry study combines topics in areas such as De novo sequencing, Glycosylation and Glycan. His study looks at the relationship between De novo sequencing and topics such as Biological system, which overlap with Protein methods and Proteomics methods. His study in the fields of Deep learning under the domain of Artificial intelligence overlaps with other disciplines such as Data-independent acquisition, Data dependent, Proteomics and Supervised learning.
Bin Ma mostly deals with Computational biology, Biotechnology, Tandem mass spectrometry, Nonribosomal peptide and Chemical diversity. His Computational biology research is multidisciplinary, incorporating elements of Sequence database, Ms ms spectra and Quantitative proteomics. His research in Biotechnology intersects with topics in Genome and Bacterial genome size.
He combines Tandem mass spectrometry and Search algorithm in his studies.
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Initial sequencing and comparative analysis of the mouse genome.
Robert H. Waterston;Kerstin Lindblad-Toh;Ewan Birney;Jane Rogers.
Genome sequence of the Brown Norway rat yields insights into mammalian evolution
Richard A. Gibbs;George M. Weinstock;Michael L. Metzker;Donna M. Muzny.
The similarity metric
Ming Li;Xin Chen;Xin Li;Bin Ma.
IEEE Transactions on Information Theory (2004)
PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry
Bin Ma;Kaizhong Zhang;Christopher Hendrie;Chengzhi Liang.
Rapid Communications in Mass Spectrometry (2003)
PatternHunter: faster and more sensitive homology search
Bin Ma;John Tromp;Ming Li.
Clustering by compression
Ming Li;Xin Chen;Xin Li;Bin Ma.
international symposium on information theory (2003)
PEAKS DB: De Novo Sequencing Assisted Database Search for Sensitive and Accurate Peptide Identification
Jing Zhang;Lei Xin;Baozhen Shan;Weiwu Chen.
Molecular & Cellular Proteomics (2012)
SPIDER: software for protein identification from sequence tags with de novo sequencing error.
Yonghua Han;Bin Ma;Kaizhong Zhang.
Journal of Bioinformatics and Computational Biology (2005)
Distinguishing string selection problems
J. Kevin Lanctot;Ming Li;Bin Ma;Shaojiu Wang.
Information & Computation (2003)
Patternhunter II: highly sensitive and fast homology search.
Ming Li;Bin Ma;Derek Kisman;John Tromp.
Journal of Bioinformatics and Computational Biology (2004)
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