Multivariate normal approximation with stein's method of exchangeable pairs under a general linearity condition
Reinert, G
Röllin, A
Annals of Probability
volume 37
issue 6
2150-2173
(01 Nov 2009)
The power of detecting enriched patterns: An HMM approach
Zhai, Z
Ku, S
Luan, Y
Reinert, G
Waterman, M
Sun, F
Journal of Computational Biology
volume 17
issue 4
581-592
(01 Apr 2010)
Random subgraph counts and u-statistics: Multivariate normal approximation via exchangeable pairs and embedding
Reinert, G
Röllin, A
Journal of Applied Probability
volume 47
issue 2
378-393
(01 Jun 2010)
Invariance principles for homogeneous sums: Universality of gaussian wiener chaos
Nourdin, I
Peccati, G
Reinert, G
Annals of Probability
volume 38
issue 5
1947-1985
(01 Sep 2010)
A boosting approach to structure learning of graphs with and without prior knowledge
Anjum, S
Doucet, A
Holmes, C
Bioinformatics
volume 25
issue 22
2929-2936
(15 Nov 2009)
How threshold behaviour affects the use of subgraphs for network comparison.
Rito, T
Wang, Z
Deane, C
Reinert, G
Bioinformatics
volume 26
issue 18
i611-i617
(15 Sep 2010)
https://www.ncbi.nlm.nih.gov/pubmed/20823329
On the length of the longest exact position match in a random sequence.
Reinert, G
Waterman, M
IEEE/ACM Trans Comput Biol Bioinform
volume 4
issue 1
153-156
(2007)
https://www.ncbi.nlm.nih.gov/pubmed/17277422
A statistical approach using network structure in the prediction of protein characteristics.
Chen, P
Deane, C
Reinert, G
Bioinformatics
volume 23
issue 17
2314-2321
(01 Sep 2007)
https://www.ncbi.nlm.nih.gov/pubmed/17599931
Predicting and validating protein interactions using network structure.
Chen, P
Deane, C
Reinert, G
PLoS Comput Biol
volume 4
issue 7
e1000118
(25 Jul 2008)
https://www.ncbi.nlm.nih.gov/pubmed/18654616
Alignment-free sequence comparison (I): statistics and power.
Reinert, G
Chew, D
Sun, F
Waterman, M
J Comput Biol
volume 16
issue 12
1615-1634
(Dec 2009)
https://www.ncbi.nlm.nih.gov/pubmed/20001252