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1 y enriched among 103,466 intragenic sites (P(hypergeometric) = 0.006; P(permutation) = 0.006).
2 imal gene networks and the GWAB gene list (P(hypergeometric )= 1.28E-09 and 4.10E-18, respectively).
3 including > or = 240 000 articles at PubMed, hypergeometric and GSEA-like enrichment statistics, pipe
4                                              Hypergeometric and permutation tests were used to determ
5 cientific disciplines: multinomial, Poisson, hypergeometric, and Bernoulli product.
6   Multiple approaches were used, including a hypergeometric based scoring system that rewards common
7  is placed on binomial-, beta-binomial-, and hypergeometric-based sampling strategies as they pertain
8 nrichment Motif Searching (GEMS) that uses a hypergeometric-based scoring function and a position-wei
9 mary, we propose that the characteristics of hypergeometric connectivity provide a coherent explanato
10 ursor masses using a peak score based on the hypergeometric distribution and an intensity score utili
11                                          The hypergeometric distribution constitutes null hypothesis-
12                     Further analysis using a hypergeometric distribution indicated that polymorphic s
13                             It relies on the hypergeometric distribution model to discover key phrase
14                    Using the assumption of a hypergeometric distribution of hotspot mutations among b
15 c model for peptide identification that uses hypergeometric distribution to approximate fragment ion
16       Our procedure uses Fisher's noncentral hypergeometric distribution to generate permuted data se
17                         The method employs a hypergeometric distribution to model frequencies of matc
18                                          The hypergeometric distribution used by the standard method
19                     The test is based on the hypergeometric distribution, which naturally arises as t
20 ted from randomly overlapping pixels given a hypergeometric distribution.
21 small RNA clusters by evaluating P-values of hypergeometric distribution.
22 m using the multivariate Fisher's noncentral hypergeometric distribution.
23                             It is shown that hypergeometric distributions minimize a range of measure
24 ion is a mixture of the Poisson and negative hypergeometric distributions, which reflects mRNAs obtai
25           Traditional enrichment tests (e.g. hypergeometric) do not account for this bias and inflate
26                                        Using hypergeometric enrichment of DEGs in Broad Hallmark gene
27 ment p-value of these terms generated from a hypergeometric enrichment test.
28  PROTein RECovery, Functional Class Scoring, Hypergeometric Enrichment, and Gene Set Enrichment Analy
29                                          The hypergeometric formula determined sample sizes and cut-o
30 arithmetic relations between values of p+1Fp hypergeometric functions and their values are analyzed.
31  novel asymptotic expansions of the required hypergeometric functions are provided to make evaluation
32 APoP with other popular methods, including a hypergeometric model (used in ChIA-PET tool), MICC (used
33                  The scores generated by the hypergeometric model do not have a significant molecular
34                 To check the validity of the hypergeometric model in describing fragment ion matches,
35 -based probability methods (like Poisson and hypergeometric models) are the most specific for matchin
36 erence between brain regions using rank-rank hypergeometric orderlap.
37                                    Rank-rank-hypergeometric overlap (RRHO), a threshold-free approach
38  a threshold-free algorithm called Rank-rank Hypergeometric Overlap (RRHO).
39                                    Rank-rank hypergeometric overlap analyses revealed extensive overl
40 ly significant overlap with published cases (hypergeometric p = 4.4e-13).
41  We identified 93 statistically significant (hypergeometric p-value < 0.01) lipidome-genotype relatio
42                                              Hypergeometric P-value analysis showed that hundreds of
43 ape plot that tracks occurrence biases using hypergeometric P-values for all words across the gene ra
44 d for the gene-enriched data using two-sided hypergeometrics (p-value).
45                              Here we use the hypergeometric phenotypic model to show that sympatric s
46                 This article shows that this hypergeometric polygenic model also approximates polygen
47 l example illustrates the application of the hypergeometric polygenic model to risk prediction under
48 nomial and multinomial models, which use the hypergeometric probabilities and cross-correlation score
49 istribution of frequencies and corresponding hypergeometric probabilities are generated for each tand
50 in the database (the null hypothesis) or the hypergeometric probability scores of the protein's pepti
51 genes with related functions, the cumulative hypergeometric probability was calculated by obtaining t
52 ons from earlier algorithms, which implement hypergeometric probability, Poisson's model, and cross-c
53                                              Hypergeometric, rank tail-strength and gene-set enrichme
54 , and machine learning results supported the hypergeometric ranking findings.
55 ic numbers as rapidly convergent generalized hypergeometric series in rational parameters.
56 consolidates both approaches by performing a hypergeometric statistical test to enrich the top NN GO
57                                            A hypergeometric tail probability for the chance occurrenc
58 epresentation analysis (ORA), which uses the hypergeometric test (or its variants) to evaluate whethe
59 ent (~134%) than either ranking based on the hypergeometric test (~109%) or occurrence ranking (~46%)
60                                      Using a hypergeometric test for concordance, the MNNG-induced ho
61                                          The hypergeometric test of enrichment was not significant at
62 tatistical test that extends the widely used Hypergeometric test of gene set enrichment to account fo
63 nder-representation using either a classical hypergeometric test or a conditional hypergeometric that
64 th drug and drug classes using a conditional hypergeometric test that adjusts for dependencies among
65 xpressed and methylated genes (P = 6.42e-09, hypergeometric test) enriched in pathways linked to insu
66 ver, the standard ORA, which is based on the hypergeometric test, analyzes each GO term in isolation
67  Ontology (GO) categories using the standard hypergeometric test, by randomly sampling non-coding ele
68  community, is a major problem for classical hypergeometric test-based ORA approaches, which cannot a
69  gene-set enrichment analysis (GSEA) and the hypergeometric test.
70 ages within and between the two species by a hypergeometric test.
71  reduce false positive rate when compared to hypergeometric test.
72 e test and (ii) a permutation-based weighted hypergeometric test.
73 algorithm, gene set enrichment analysis, and hypergeometric test; using this method, we identified 50
74                                        Then, hypergeometrics test and random walks with restart (RWR)
75 CGs and 280 lncRNAs on a broader scale using hypergeometrics test and RWR.
76 cs than their own pre-viral-challenge state (hypergeometric-test: p=0.029).
77 d by their inter-domain integration based on hypergeometric tests of the number of shared individuals
78                             ToppCluster uses hypergeometric tests to obtain list-specific feature enr
79 assical hypergeometric test or a conditional hypergeometric that uses the relationships among GO term