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Items: 13

1.

Efficient multi-task chemogenomics for drug specificity prediction.

Playe B, Azencott CA, Stoven V.

PLoS One. 2018 Oct 4;13(10):e0204999. doi: 10.1371/journal.pone.0204999. eCollection 2018.

2.

Machine learning and genomics: precision medicine versus patient privacy.

Azencott CA.

Philos Trans A Math Phys Eng Sci. 2018 Sep 13;376(2128). pii: 20170350. doi: 10.1098/rsta.2017.0350. Review.

PMID:
30082298
3.

The inconvenience of data of convenience: computational research beyond post-mortem analyses.

Azencott CA, Aittokallio T, Roy S; DREAM Idea Challenge Consortium, Norman T, Friend S, Stolovitzky G, Goldenberg A.

Nat Methods. 2017 Sep 29;14(10):937-938. doi: 10.1038/nmeth.4457. No abstract available.

PMID:
28960198
4.

Erratum: Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.

Sieberts SK, Zhu F, García-García J, Stahl E, Pratap A, Pandey G, Pappas D, Aguilar D, Anton B, Bonet J, Eksi R, Fornés O, Guney E, Li H, Marín MA, Panwar B, Planas-Iglesias J, Poglayen D, Cui J, Falcao AO, Suver C, Hoff B, Balagurusamy VS, Dillenberger D, Neto EC, Norman T, Aittokallio T, Ammad-Ud-Din M, Azencott CA, Bellón V, Boeva V, Bunte K, Chheda H, Cheng L, Corander J, Dumontier M, Goldenberg A, Gopalacharyulu P, Hajiloo M, Hidru D, Jaiswal A, Kaski S, Khalfaoui B, Khan SA, Kramer ER, Marttinen P, Mezlini AM, Molparia B, Pirinen M, Saarela J, Samwald M, Stoven V, Tang H, Tang J, Torkamani A, Vert JP, Wang B, Wang T, Wennerberg K, Wineinger NE, Xiao G, Xie Y, Yeung R, Zhan X, Zhao C; Members of the Rheumatoid Arthritis Challenge Consortium, Greenberg J, Kremer J, Michaud K, Barton A, Coenen M, Mariette X, Miceli C, Shadick N, Weinblatt M, de Vries N, Tak PP, Gerlag D, Huizinga TW, Kurreeman F, Allaart CF, Bridges SL Jr, Criswell L, Moreland L, Klareskog L, Saevarsdottir S, Padyukov L, Gregersen PK, Friend S, Plenge R, Stolovitzky G, Oliva B, Guan Y, Mangravite LM.

Nat Commun. 2016 Oct 10;7:13205. doi: 10.1038/ncomms13205. No abstract available.

5.

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.

Sieberts SK, Zhu F, García-García J, Stahl E, Pratap A, Pandey G, Pappas D, Aguilar D, Anton B, Bonet J, Eksi R, Fornés O, Guney E, Li H, Marín MA, Panwar B, Planas-Iglesias J, Poglayen D, Cui J, Falcao AO, Suver C, Hoff B, Balagurusamy VS, Dillenberger D, Neto EC, Norman T, Aittokallio T, Ammad-Ud-Din M, Azencott CA, Bellón V, Boeva V, Bunte K, Chheda H, Cheng L, Corander J, Dumontier M, Goldenberg A, Gopalacharyulu P, Hajiloo M, Hidru D, Jaiswal A, Kaski S, Khalfaoui B, Khan SA, Kramer ER, Marttinen P, Mezlini AM, Molparia B, Pirinen M, Saarela J, Samwald M, Stoven V, Tang H, Tang J, Torkamani A, Vert JP, Wang B, Wang T, Wennerberg K, Wineinger NE, Xiao G, Xie Y, Yeung R, Zhan X, Zhao C; Members of the Rheumatoid Arthritis Challenge Consortium, Greenberg J, Kremer J, Michaud K, Barton A, Coenen M, Mariette X, Miceli C, Shadick N, Weinblatt M, de Vries N, Tak PP, Gerlag D, Huizinga TW, Kurreeman F, Allaart CF, Louis Bridges S Jr, Bridges SL, Criswell L, Moreland L, Klareskog L, Saevarsdottir S, Padyukov L, Gregersen PK, Friend S, Plenge R, Stolovitzky G, Oliva B, Guan Y, Mangravite LM.

Nat Commun. 2016 Aug 23;7:12460. doi: 10.1038/ncomms12460. Erratum in: Nat Commun. 2016 Oct 10;7:13205.

6.

MULTITASK FEATURE SELECTION WITH TASK DESCRIPTORS.

Bellón V, Stoven V, Azencott CA.

Pac Symp Biocomput. 2016;21:261-72.

7.

The evaluation of tools used to predict the impact of missense variants is hindered by two types of circularity.

Grimm DG, Azencott CA, Aicheler F, Gieraths U, MacArthur DG, Samocha KE, Cooper DN, Stenson PD, Daly MJ, Smoller JW, Duncan LE, Borgwardt KM.

Hum Mutat. 2015 May;36(5):513-23. doi: 10.1002/humu.22768. Epub 2015 Mar 26.

8.

Efficient network-guided multi-locus association mapping with graph cuts.

Azencott CA, Grimm D, Sugiyama M, Kawahara Y, Borgwardt KM.

Bioinformatics. 2013 Jul 1;29(13):i171-9. doi: 10.1093/bioinformatics/btt238.

9.

GLIDE: GPU-based linear regression for detection of epistasis.

Kam-Thong T, Azencott CA, Cayton L, Pütz B, Altmann A, Karbalai N, Sämann PG, Schölkopf B, Müller-Myhsok B, Borgwardt KM.

Hum Hered. 2012;73(4):220-36. Epub 2012 Sep 4.

10.

Learning to predict chemical reactions.

Kayala MA, Azencott CA, Chen JH, Baldi P.

J Chem Inf Model. 2011 Sep 26;51(9):2209-22. doi: 10.1021/ci200207y. Epub 2011 Sep 2.

11.

A CROC stronger than ROC: measuring, visualizing and optimizing early retrieval.

Swamidass SJ, Azencott CA, Daily K, Baldi P.

Bioinformatics. 2010 May 15;26(10):1348-56. doi: 10.1093/bioinformatics/btq140. Epub 2010 Apr 7.

12.

Influence relevance voting: an accurate and interpretable virtual high throughput screening method.

Swamidass SJ, Azencott CA, Lin TW, Gramajo H, Tsai SC, Baldi P.

J Chem Inf Model. 2009 Apr;49(4):756-66. doi: 10.1021/ci8004379.

13.

One- to four-dimensional kernels for virtual screening and the prediction of physical, chemical, and biological properties.

Azencott CA, Ksikes A, Swamidass SJ, Chen JH, Ralaivola L, Baldi P.

J Chem Inf Model. 2007 May-Jun;47(3):965-74. Epub 2007 Mar 6.

PMID:
17338509

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