Probabilistic Sequencing Models
Probabilistic Sequencing Models is a computational framework that belongs to the class of de novo peptide sequencing methods and specifically employs statistical inference and probability distributions to determine the most likely amino acid sequence from tandem mass spectrometry data, distinguishing itself by quantifying uncertainty and incorporating probabilistic dependencies among spectral events and sequence hypotheses.
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11
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2017–2026
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Some thoughts on counts in sequencing studies
Juan José Egozcue, Jan Graffelman, M. I. Ortego et al. · NAR Genomics and Bioinformatics · 2020 · 17 citations · Full text
Immune response of infants in tropics to injectable polio vaccine.
Rohini Krishnan, M Jadhav, R Selvakumar et al. · BMJ · 1982 · 12 citations · Full text
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University of Cambridge
Cambridge, United Kingdom
1 h-index
2 publications
36 citations
Christian Medical College
Ludhiana, India
1 h-index
3 publications
36 citations

University of Oslo
Oslo, Norway
1 h-index
1 publications
21 citations
Signal Processing (United States)
Rockville, United States
1 h-index
2 publications
36 citations
Universitat Politècnica de Catalunya
Barcelona, Spain
1 h-index
3 publications
51 citations
Oslo University Hospital
Oslo, Norway
1 h-index
2 publications
42 citations
The University of Texas at Austin
Austin, United States
1 h-index
2 publications
32 citations
Indian Council of Medical Research
New Delhi, India
1 h-index
3 publications
36 citations
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Conference · 1 publications · 18 citations
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FSI · 1 publications · 21 citations
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1 publications · 12 citations
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1 publications · 17 citations
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1 publications · 16 citations
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