Publication Search Results
Exact matches for:
- Author = Keich U [web profile page]
1.
Freestone J, Noble WS, Keich U
Jack Freestone, William Stafford Noble, Uri Keich:
Reinvestigating the Correctness of Decoy-Based False Discovery Rate Control in Proteomics Tandem Mass Spectrometry,
Journal of Proteome Research,
23
(2024),
no. 6,
1907–1914.
2.
Luo D, Ebadi A, Emery K, He Y, Noble WS, Keich U
Dong Luo, Arya Ebadi, Kristen Emery, Yilun He, William Stafford Noble, Uri Keich:
Competition-based control of the false discovery proportion,
Biometrics,
79
(2023),
no. 4,
3472–3484.
3.
Rajchert A, Keich U
Andrew Rajchert, Uri Keich:
Controlling the false discovery rate via competition: Is the +1 needed?,
Statistics and Probability Letters,
197
(2023),
Article 109819 (7 pages).
4.
Peres N, Lee AR, Keich U
Noah Peres, Andrew Ray Lee, Uri Keich:
Exactly Computing the Tail of the Poisson-Binomial Distribution,
ACM Transactions on Mathematical Software,
47 Open Access
(2021),
no. 4,
1–19.
5.
Emery K, Hasam S, Noble WS, Keich U
Kristen Emery, Syamand Hasam, William Stafford Noble and Uri Keich:
Multiple Competition-Based FDR Control and Its Application to Peptide Detection,
Lecture Notes in Computer Science,
12074
(2020),
no. RECOMB 2020,
54–71.
6.
Keich U, Tamura K, Noble WS
Uri Keich, Kaipo Tamura and William Stafford Noble:
Averaging Strategy To Reduce Variability in Target-Decoy Estimates of False Discovery Rate,
Journal of Proteome Research,
18
(2019),
no. 2,
585–593.
7.
Keich U, Noble WS
Uri Keich and William Stafford Noble:
Controlling the FDR in Imperfect Matches to an Incomplete Database,
Journal of the American Statistical Association,
113
(2018),
no. 523,
973–982.
8.
Noble WS, Keich U
William Stafford Noble and Uri Keich:
Response to "Mass spectrometrists should search for all peptides, but assess only the ones they care about",
Nature Methods,
14
(2017),
no. 7,
Page 644.
9.
Wilson H, Keich U
Huon Wilson and Uri Keich:
Accurate Small Tail Probabilities of Sums of iid Lattice-Valued Random Variables via FFT,
Journal of Computational and Graphical Statistics,
26
(2017),
no. 1,
223–229.
10.
Manescu D, Keich U
David Manescu and Uri Keich:
A Symmetric Length-Aware Enrichment Test,
Journal of Computational Biology,
23
(2016),
no. 6,
508–525.
MR3512807
11.
Wilson H, Keich U
Huon Wilson and Uri Keich:
Accurate pairwise convolutions of non-negative vectors via FFT,
Computational Statistics and Data Anaysis,
101
(2016),
300–315.
MR3504852
12.
Manescu D, Keich U
David Manescu and Uri Keich:
A Symmetric Length-Aware Enrichment Test,
Lecture Notes in Computer Science,
9029
(2015),
224–242.
13.
Keich U, Kertesz-Farkas A, Noble WS
U Keich, A Kertesz-Farkas, W S Noble:
Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics,
Journal of Proteome Research,
14
(2015),
no. 8,
3148–3161.
14.
Kertesz-Farkas A, Keich U, Noble WS
A Kertesz-Farkas, U Keich, W S Noble:
Tandem Mass Spectrum Identification via Cascaded Search,
Journal of Proteome Research,
14
(2015),
no. 8,
3027–3038.
15.
Tanaka E, Bailey TL, Keich U
Emi Tanaka, Timothy L Bailey and Uri Keich:
Improving MEME via a two-tiered significance analysis,
Bioinformatics,
30
(2014),
no. 14,
1965–1973.
16.
Liachko I, Youngblood RA, Keich U, Dunham MJ
I Liachko, R A Youngblood, U Keich, M J Dunham:
High-resolution mapping, characterization, and optimization of autonomously replicating sequences in yeast,
Genome Research,
23
(2013),
no. 4,
698–704.
17.
Liachko I, Tanaka E, Cox K, Claire SC, Yang L, Seher A, Hallas L, Cha E, Kang G, Pace H, Barrow J, Inada M, Tye BK, Keich U
Ivan Liachko, Emi Tanaka, Katherine Cox, Shau Chee Claire, Lu Yang, Arael Seher, Lindsay Hallas, Eugene Cha, Gina Kang, Heather Pace, Jasmine Barrow, Maki Inada, Bik-Kwoon Tye and Uri Keich:
Novel features of ARS selection in budding yeast Lachancea kluyveri,
BMC Genomics,
12
(2011),
Art. 633.
18.
Gupta N, Bandeira N, Keich U, Pevzner PA
Nitin Gupta, Nuno Bandeira, Uri Keich, Pavel A Pevzner:
Target-Decoy Approach and False Discovery Rate: When Things May Go Wrong,
Journal of the American Society for Mass Spectrometry,
22
(2011),
1111–1120.
19.
Tanaka E, Bailey TL, Grant CE, Noble WS, Keich U
Emi Tanaka, Timothy Bailey, Charles E Grant, William Stafford Noble, Uri Keich:
Improved similarity scores for comparing motifs,
Bioinformatics,
27
(2011),
no. 12,
1603–1609.
20.
Ng P, Keich U
Patrick Ng and Uri Keich:
Alignment constrained sampling,
Journal of computational biology,
18
(2011),
no. 2,
155–168.
21.
Liachko I, Bhaskar A, Lee C, Chung SCC, Tye BK, Keich U
Ivan Liachko, Anand Bhaskar, Chanmi Lee, Shau Chee Claire Chung, Bik-Kwoon Tye, Uri Keich:
A Comprehensive Genome-Wide Map of Autonomously Replicating Sequences in a Naive Genome,
PLoS Genetics,
6
(2010),
no. 5,
e1000946.
22.
Bhaskar A, Keich U
Anand Bhaskar and Uri Keich:
Confidently estimating the number of DNA replication origins,
Statistical Applications in Genetics and Molecular Biology,
9
(2010),
no. 1,
1–21.
23.
Oliver HF, Orsi RH, Ponnala L, Keich U, Wang W, Sun Q, Cartinhour SW, Filiatrault MJ, Weidmann M, Boor KJ
Haley F Oliver, Renato H Orsi, Lalit Ponnala, Uri Keich, Wei Wang, Qi Sun, Samuel W Cartinhour, Melanie J Filiatrault, Martin Wiedmann and Kathryn J Boor:
Deep RNA sequencing of L. monocytogenes reveals overlapping and extensive stationary phase and sigma B-dependent transcriptomes, including multiple highly transcribed noncoding RNAs,
BMC Genomics,
10
(2009),
641.
24.
Nagarajan N, Keich U
Niranjan Nagarajan and Uri Keich:
Reliability and efficiency of algorithms for computing the significance of the Mann--Whitney test,
Computational Statistics,
24
(2009),
no. 4,
605–622.
25.
Nagarajan N, Ng P, Keich U
Nagarajan N., Ng P., and Keich U:
Refining motif finders with E-value calculations,
3rd RECOMB Satellite Workshop on Regulatory Genomics,
NA (ed.),
NA,
(2008),
NA.
MR2273480
26.
Nagarajan N, Keich U
N Nagarajan, U Keich:
FAST: Fourier transform based Algorithms for significance testing of ungapped multiple alignments,
Bioinformatics,
24
(2008),
no. 4,
577–578.
27.
Keich U, Gao H, Garretson JS, Bhaskar A, Liachko I, Donato J, Tye BK
U Keich, H Gao, JS Garretson, A Bhaskar, I Liachko, J Donato, B Tye:
Computational detection of significant variation in binding affinity across two sets of sequences with application to the analysis of replication origins in yeast,
BMC Bioinformatics,
9
(2008),
372.
28.
Ng P, Keich U
P Ng, U Keich:
GIMSAN: a Gibbs motif finder with significance analysis,
Bioinformatics,
24
(2008),
no. 19,
2256–2257.
29.
Ng P, Keich U
P Ng, U Keich:
Factoring local sequence composition in motif significance analysis,
Genome informatics,
21
(2008),
15–26.
30.
Zhi D, Keich U, Pevzner PA, Heber S, Tang H
D Zhi, U Keich, P Pevzner, S Heber, H Tang:
Checking for base-calling errors in repeats,
IEEE/ACM Transactions on computational biology and bioinformatics,
4
(2007),
no. 1,
54–64.
31.
Keich U, Ng P
U Keich, P Ng:
A conservative parametric approach to motif significance analysis,
Genome Informatics,
19
(2007),
61–72.
32.
Keich U, Nagarajan N
U Keich, N Nagarajan:
A fast and numerically robust method for exact multinomial goodness-of-fit test,
Journal of Computational and Graphical Statistics,
15
(2006),
no. 4,
779–802.
MR2273480
33.
Nagarajan N, Ng P, Keich U
N Nagarajan, P Ng and U Keich:
Apples to apples: improving the performance of motif finders and their significance analysis in the Twilight Zone,
Bioinformatics,
22
(2006),
no. 14,
393–401.
34.
Keich U
U Keich:
sFFT: a faster accurate computation of the p-value of the entropy score,
Journal of computational Biology,
12
(2005),
no. 4,
416–430.
35.
Buhler J, Keich U, Sun Y
J Buhler, U Keich, Y Sun:
Designing seeds for similarity search in genomic DNA,
Journal of computer and system sciences,
70
(2005),
no. 3,
342–363.
MR2129866
36.
Nagarajan N, Jones N, Keich U
N Nagarajan, N Jones and U Keich:
Computing the p-valueof the information content from an alignment of multiple sequence,
Bioinformatics,
21
(2005),
no. Suppl. 1,
i311 – i318.
37.
Keich U, Nagarajan N
Keich, U. and Nagarajan, N.:
A faster reliable algorithm to estimate the p-value of the multinomial llr statistic,
Proceeding of the 4th International Workshop on Algorithms in Bioinformatics,
WABI 2004,
NA (ed.),
NA,
NA,
(2004),
NA.
38.
Keich U, Li M, Ma B, Tromp J
U Keich, M Li, B Ma, J Tromp:
On spaced seeds for similarity search,
Discrete applied mathematics,
138
(2004),
no. 3,
253–263.
MR2049648
39.
Eskin E, Keich U, Gelfand MS, Pevzner PA
Eskin, E., Keich, U., Gelfand, M.S., Pevzner, P.A.:
Genome-Wide Analysis of Bacterial Promoter Regions,
Proceedings of the Pacific Symposium on Biocomputing 2003,
PSB 2003,
NA (ed.),
NA,
(2003),
NA.
40.
Buhler J, Keich U, Sun Y
Buhler J., Keich U., Sun Y.:
Designing Seeds for Similarity Search in Genomic DNA,
Proceedings of the Seventh Annual International Conference on Research in Computational Molecular Biology,
RECOMB 2003,
(2003),
41.
Keich U
U Keich:
Stationary tangent - the discrete and non-smooth cases,
Journal of time series analysis,
24
(2003),
no. 2,
173–192.
MR1965814
42.
Keich U, Pevzner PA
Keich, U. and Pevzner, P.A.:
Finding motifs in the twilight zone,
Proceedings of the Sixth Annual International Conference on Research in Computational Molecular Biology,
RECOMB 2002,
(2002),
43.
Keich U, Pevzner PA
U Keich, P A Pevzner:
Finding motifs in the twilight zone,
Bioinformatics,
18
(2002),
no. 10,
1374–1381.
44.
Keich U, Pevzner PA
U Keich, P A Pevzner:
Subtle motifs: defining the limits of motif finding algorithms,
Bioinformatics,
18
(2002),
no. 10,
1382–1390.
| Number of matches: 44 |