Format
Sort by
Items per page

Send to

Choose Destination

Search results

Items: 1 to 20 of 39

1.

Detecting gene-gene interactions using a permutation-based random forest method.

Li J, Malley JD, Andrew AS, Karagas MR, Moore JH.

BioData Min. 2016 Apr 6;9:14. doi: 10.1186/s13040-016-0093-5. eCollection 2016.

2.

r2VIM: A new variable selection method for random forests in genome-wide association studies.

Szymczak S, Holzinger E, Dasgupta A, Malley JD, Molloy AM, Mills JL, Brody LC, Stambolian D, Bailey-Wilson JE.

BioData Min. 2016 Feb 1;9:7. doi: 10.1186/s13040-016-0087-3. eCollection 2016.

3.

Synthetic learning machines.

Ishwaran H, Malley JD.

BioData Min. 2014 Dec 18;7(1):28. doi: 10.1186/s13040-014-0028-y. eCollection 2014.

4.

A Simplified Basis for Bell-Kochen-Specker Theorems.

Malley JD, Fine A.

Phys Lett A. 2014 Jul 11;378(35):2611-2613.

5.

First complex, then simple.

Malley JD, Moore JH.

BioData Min. 2014 Jul 18;7:13. doi: 10.1186/1756-0381-7-13. eCollection 2014. No abstract available.

6.

Innovation is often unnerving: the door into summer.

Malley JD, Moore JH.

BioData Min. 2014 Jul 17;7:12. doi: 10.1186/1756-0381-7-12. eCollection 2014. No abstract available.

7.

Looking for childhood-onset schizophrenia: diagnostic algorithms for classifying children and adolescents with psychosis.

Greenstein D, Kataria R, Gochman P, Dasgupta A, Malley JD, Rapoport J, Gogtay N.

J Child Adolesc Psychopharmacol. 2014 Sep;24(7):366-73. doi: 10.1089/cap.2013.0139. Epub 2014 Jul 14.

8.

Comparative validation of the D. melanogaster modENCODE transcriptome annotation.

Chen ZX, Sturgill D, Qu J, Jiang H, Park S, Boley N, Suzuki AM, Fletcher AR, Plachetzki DC, FitzGerald PC, Artieri CG, Atallah J, Barmina O, Brown JB, Blankenburg KP, Clough E, Dasgupta A, Gubbala S, Han Y, Jayaseelan JC, Kalra D, Kim YA, Kovar CL, Lee SL, Li M, Malley JD, Malone JH, Mathew T, Mattiuzzo NR, Munidasa M, Muzny DM, Ongeri F, Perales L, Przytycka TM, Pu LL, Robinson G, Thornton RL, Saada N, Scherer SE, Smith HE, Vinson C, Warner CB, Worley KC, Wu YQ, Zou X, Cherbas P, Kellis M, Eisen MB, Piano F, Kionte K, Fitch DH, Sternberg PW, Cutter AD, Duff MO, Hoskins RA, Graveley BR, Gibbs RA, Bickel PJ, Kopp A, Carninci P, Celniker SE, Oliver B, Richards S.

Genome Res. 2014 Jul;24(7):1209-23. doi: 10.1101/gr.159384.113.

9.

SCORHE: a novel and practical approach to video monitoring of laboratory mice housed in vivarium cage racks.

Salem GH, Dennis JU, Krynitsky J, Garmendia-Cedillos M, Swaroop K, Malley JD, Pajevic S, Abuhatzira L, Bustin M, Gillet JP, Gottesman MM, Mitchell JB, Pohida TJ.

Behav Res Methods. 2015 Mar;47(1):235-50. doi: 10.3758/s13428-014-0451-5.

10.

Risk estimation using probability machines.

Dasgupta A, Szymczak S, Moore JH, Bailey-Wilson JE, Malley JD.

BioData Min. 2014 Mar 1;7(1):2. doi: 10.1186/1756-0381-7-2.

11.

A system-level pathway-phenotype association analysis using synthetic feature random forest.

Pan Q, Hu T, Malley JD, Andrew AS, Karagas MR, Moore JH.

Genet Epidemiol. 2014 Apr;38(3):209-19. doi: 10.1002/gepi.21794. Epub 2014 Feb 17.

12.

Probability estimation with machine learning methods for dichotomous and multicategory outcome: theory.

Kruppa J, Liu Y, Biau G, Kohler M, König IR, Malley JD, Ziegler A.

Biom J. 2014 Jul;56(4):534-63. doi: 10.1002/bimj.201300068. Epub 2014 Jan 29. Review.

PMID:
24478134
13.

O brave new world that has such machines in it.

Malley JD, Malley KG, Moore JH.

BioData Min. 2014 Nov 17;7:26. doi: 10.1186/1756-0381-7-26. eCollection 2014. No abstract available.

14.

The disconnect between classical biostatistics and the biological data mining community.

Malley JD, Moore JH.

BioData Min. 2013 Jul 24;6(1):12. doi: 10.1186/1756-0381-6-12. No abstract available.

15.

The limits of p-values for biological data mining.

Malley JD, Dasgupta A, Moore JH.

BioData Min. 2013 May 11;6(1):10. doi: 10.1186/1756-0381-6-10. No abstract available.

16.

The clinical phenotypes of the juvenile idiopathic inflammatory myopathies.

Shah M, Mamyrova G, Targoff IN, Huber AM, Malley JD, Rice MM, Miller FW, Rider LG; Childhood Myositis Heterogeneity Collaborative Study Group.

Medicine (Baltimore). 2013 Jan;92(1):25-41. doi: 10.1097/MD.0b013e31827f264d.

17.

Using multivariate machine learning methods and structural MRI to classify childhood onset schizophrenia and healthy controls.

Greenstein D, Malley JD, Weisinger B, Clasen L, Gogtay N.

Front Psychiatry. 2012 Jun 1;3:53. doi: 10.3389/fpsyt.2012.00053. eCollection 2012.

18.

Performance of random forests and logic regression methods using mini-exome sequence data.

Kim Y, Li Q, Cropp CD, Sung H, Cai J, Simpson CL, Perry B, Dasgupta A, Malley JD, Wilson AF, Bailey-Wilson JE.

BMC Proc. 2011 Nov 29;5 Suppl 9:S104. doi: 10.1186/1753-6561-5-S9-S104.

19.

Brief review of regression-based and machine learning methods in genetic epidemiology: the Genetic Analysis Workshop 17 experience.

Dasgupta A, Sun YV, König IR, Bailey-Wilson JE, Malley JD.

Genet Epidemiol. 2011;35 Suppl 1:S5-11. doi: 10.1002/gepi.20642. Review.

20.

The behaviour of random forest permutation-based variable importance measures under predictor correlation.

Nicodemus KK, Malley JD, Strobl C, Ziegler A.

BMC Bioinformatics. 2010 Feb 27;11:110. doi: 10.1186/1471-2105-11-110.

Supplemental Content

Loading ...
Support Center