 Connection
Katerina Kechris to High-Throughput Nucleotide Sequencing
This is a "connection" page, showing publications Katerina Kechris has written about High-Throughput Nucleotide Sequencing.
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Connection Strength |
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1.518 |
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Russell PH, Vestal B, Shi W, Rudra PD, Dowell R, Radcliffe R, Saba L, Kechris K. miR-MaGiC improves quantification accuracy for small RNA-seq. BMC Res Notes. 2018 May 15; 11(1):296.
Score: 0.458
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Rudra P, Shi WJ, Vestal B, Russell PH, Odell A, Dowell RD, Radcliffe RA, Saba LM, Kechris K. Model based heritability scores for high-throughput sequencing data. BMC Bioinformatics. 2017 Mar 02; 18(1):143.
Score: 0.421
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Siska C, Kechris K. Differential correlation for sequencing data. BMC Res Notes. 2017 Jan 19; 10(1):54.
Score: 0.418
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Lusk R, Stene E, Banaei-Kashani F, Tabakoff B, Kechris K, Saba LM. Aptardi predicts polyadenylation sites in sample-specific transcriptomes using high-throughput RNA sequencing and DNA sequence. Nat Commun. 2021 03 12; 12(1):1652.
Score: 0.139
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De S, Pedersen BS, Kechris K. The dilemma of choosing the ideal permutation strategy while estimating statistical significance of genome-wide enrichment. Brief Bioinform. 2014 Nov; 15(6):919-28.
Score: 0.082
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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