Syotti: scalable bait design for DNA enrichment is a research paper published in Bioinformatics (2022). On theSindex it has a DataRank of 0.442. It has been cited 18 times.
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Base Score Contribution
0.442
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →NSERC
Grant: RGPIN-07185-2020
NIH NIAID
Grant: R01HG011392
National Science Foundation Smart and Connected Health Integrative Projects
Grant: 2013998
SCH: INT: Enabling real time surveillance of antimicrobial resistance
National Science Foundation Early-concept Grants for Exploratory Research
Grant: 2118251
Collaborative Research: EAGER: Solving the bait learning problem for large-scale DNA enrichment
Agencia Nacional de Investigación y Desarrollo
Grant: FB0001
U.S-Israel Binational Science Foundation
Grant: 2018302
National Science Foundation
Grant: CCF-2008838
NIAID NIH HHS
Grant: R01 AI141810
Natural Sciences and Engineering Research Council of Canada
Grant: unidentified
unidentified
Research Council of Finland
Grant: 351145
Massively Parallel Algorithms and Analysis for Metagenomics and Pangenomics (MAPAMEPA)
National Science Foundation
Grant: 2008838
AF: Small: Algorithms meet Structural Graph Decomposition
Research Council of Finland
Grant: 336092
Design and Verification Methods for Massively Parallel Distributed Systems (DeVeMaPa)
National Institutes of Health
Grant: 2R01HG011392-06
Personal and panel references for improved alignment
Natural Sciences and Engineering Research Council of Canada
National Institute of Allergy and Infectious Diseases
National Institutes of Health
FWCI
1.09
Citation Percentile
0.8%
Citation Trend
Fields of Study
MeSH Terms
Keywords