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Items: 1 to 50 of 66

1.

Depression, depressive symptoms and treatments in women who have recently given birth: UK cohort study.

Petersen I, Peltola T, Kaski S, Walters KR, Hardoon S.

BMJ Open. 2018 Oct 24;8(10):e022152. doi: 10.1136/bmjopen-2018-022152.

2.

Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge.

Sundin I, Peltola T, Micallef L, Afrabandpey H, Soare M, Mamun Majumder M, Daee P, He C, Serim B, Havulinna A, Heckman C, Jacucci G, Marttinen P, Kaski S.

Bioinformatics. 2018 Jul 1;34(13):i395-i403. doi: 10.1093/bioinformatics/bty257.

3.

Development of Full Sweet, Umami, and Bitter Taste Responsiveness Requires Regulator of G protein Signaling-21 (RGS21).

Schroer AB, Gross JD, Kaski SW, Wix K, Siderovski DP, Vandenbeuch A, Setola V.

Chem Senses. 2018 May 23;43(5):367-378. doi: 10.1093/chemse/bjy024.

PMID:
29701767
4.

Phenotype-driven identification of epithelial signalling clusters.

Marques E, Peltola T, Kaski S, Klefström J.

Sci Rep. 2018 Mar 5;8(1):4034. doi: 10.1038/s41598-018-22293-x.

5.

Efficient differentially private learning improves drug sensitivity prediction.

Honkela A, Das M, Nieminen A, Dikmen O, Kaski S.

Biol Direct. 2018 Feb 6;13(1):1. doi: 10.1186/s13062-017-0203-4.

6.

Regulator of G protein signaling-12 modulates the dopamine transporter in ventral striatum and locomotor responses to psychostimulants.

Gross JD, Kaski SW, Schroer AB, Wix KA, Siderovski DP, Setola V.

J Psychopharmacol. 2018 Feb;32(2):191-203. doi: 10.1177/0269881117742100. Epub 2018 Jan 24.

PMID:
29364035
7.

A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines.

Gönen M, Weir BA, Cowley GS, Vazquez F, Guan Y, Jaiswal A, Karasuyama M, Uzunangelov V, Wang T, Tsherniak A, Howell S, Marbach D, Hoff B, Norman TC, Airola A, Bivol A, Bunte K, Carlin D, Chopra S, Deran A, Ellrott K, Gopalacharyulu P, Graim K, Kaski S, Khan SA, Newton Y, Ng S, Pahikkala T, Paull E, Sokolov A, Tang H, Tang J, Wennerberg K, Xie Y, Zhan X, Zhu F; Broad-DREAM Community, Aittokallio T, Mamitsuka H, Stuart JM, Boehm JS, Root DE, Xiao G, Stolovitzky G, Hahn WC, Margolin AA.

Cell Syst. 2017 Nov 22;5(5):485-497.e3. doi: 10.1016/j.cels.2017.09.004. Epub 2017 Oct 4.

PMID:
28988802
8.

MediSyn: uncertainty-aware visualization of multiple biomedical datasets to support drug treatment selection.

He C, Micallef L, Tanoli ZU, Kaski S, Aittokallio T, Jacucci G.

BMC Bioinformatics. 2017 Sep 13;18(Suppl 10):393. doi: 10.1186/s12859-017-1785-7.

9.

A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury.

Kohonen P, Parkkinen JA, Willighagen EL, Ceder R, Wennerberg K, Kaski S, Grafström RC.

Nat Commun. 2017 Jul 3;8:15932. doi: 10.1038/ncomms15932.

10.

Fundamentals and Recent Developments in Approximate Bayesian Computation.

Lintusaari J, Gutmann MU, Dutta R, Kaski S, Corander J.

Syst Biol. 2017 Jan 1;66(1):e66-e82. doi: 10.1093/sysbio/syw077.

11.

Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals.

Eugster MJ, Ruotsalo T, Spapé MM, Barral O, Ravaja N, Jacucci G, Kaski S.

Sci Rep. 2016 Dec 8;6:38580. doi: 10.1038/srep38580.

12.

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.

13.

Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization.

Ammad-Ud-Din M, Khan SA, Malani D, Murumägi A, Kallioniemi O, Aittokallio T, Kaski S.

Bioinformatics. 2016 Sep 1;32(17):i455-i463. doi: 10.1093/bioinformatics/btw433.

PMID:
27587662
14.

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.

15.

Sparse group factor analysis for biclustering of multiple data sources.

Bunte K, Leppäaho E, Saarinen I, Kaski S.

Bioinformatics. 2016 Aug 15;32(16):2457-63. doi: 10.1093/bioinformatics/btw207. Epub 2016 Apr 19.

PMID:
27153643
16.

Modelling-based experiment retrieval: a case study with gene expression clustering.

Blomstedt P, Dutta R, Seth S, Brazma A, Kaski S.

Bioinformatics. 2016 May 1;32(9):1388-94. doi: 10.1093/bioinformatics/btv762. Epub 2016 Jan 6.

PMID:
26740526
17.

On the Identifiability of Transmission Dynamic Models for Infectious Diseases.

Lintusaari J, Gutmann MU, Kaski S, Corander J.

Genetics. 2016 Mar;202(3):911-8. doi: 10.1534/genetics.115.180034. Epub 2016 Jan 6.

18.

Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of 'Omics' Data from Human Cell Cultures.

Grafström RC, Nymark P, Hongisto V, Spjuth O, Ceder R, Willighagen E, Hardy B, Kaski S, Kohonen P.

Altern Lab Anim. 2015 Nov;43(5):325-32.

PMID:
26551289
19.

Kernelized Bayesian Matrix Factorization.

Gönen M, Kaski S.

IEEE Trans Pattern Anal Mach Intell. 2014 Oct;36(10):2047-60. doi: 10.1109/TPAMI.2014.2313125.

PMID:
26352634
20.

Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals.

Kauppi JP, Kandemir M, Saarinen VM, Hirvenkari L, Parkkonen L, Klami A, Hari R, Kaski S.

Neuroimage. 2015 May 15;112:288-298. doi: 10.1016/j.neuroimage.2014.12.079. Epub 2015 Jan 13.

PMID:
25595505
21.

Group Factor Analysis.

Klami A, Virtanen S, Leppäaho E, Kaski S.

IEEE Trans Neural Netw Learn Syst. 2015 Sep;26(9):2136-47. doi: 10.1109/TNNLS.2014.2376974. Epub 2014 Dec 18.

22.

Toward computational cumulative biology by combining models of biological datasets.

Faisal A, Peltonen J, Georgii E, Rung J, Kaski S.

PLoS One. 2014 Nov 26;9(11):e113053. doi: 10.1371/journal.pone.0113053. eCollection 2014.

23.

Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysis.

Khan SA, Virtanen S, Kallioniemi OP, Wennerberg K, Poso A, Kaski S.

Bioinformatics. 2014 Sep 1;30(17):i497-504. doi: 10.1093/bioinformatics/btu456.

24.

Stronger findings for metabolomics through Bayesian modeling of multiple peaks and compound correlations.

Suvitaival T, Rogers S, Kaski S.

Bioinformatics. 2014 Sep 1;30(17):i461-7. doi: 10.1093/bioinformatics/btu455.

25.

Integrative and personalized QSAR analysis in cancer by kernelized Bayesian matrix factorization.

Ammad-ud-din M, Georgii E, Gönen M, Laitinen T, Kallioniemi O, Wennerberg K, Poso A, Kaski S.

J Chem Inf Model. 2014 Aug 25;54(8):2347-59. doi: 10.1021/ci500152b. Epub 2014 Aug 6.

PMID:
25046554
26.

Stronger findings from mass spectral data through multi-peak modeling.

Suvitaival T, Rogers S, Kaski S.

BMC Bioinformatics. 2014 Jun 19;15:208. doi: 10.1186/1471-2105-15-208.

27.

A community effort to assess and improve drug sensitivity prediction algorithms.

Costello JC, Heiser LM, Georgii E, Gönen M, Menden MP, Wang NJ, Bansal M, Ammad-ud-din M, Hintsanen P, Khan SA, Mpindi JP, Kallioniemi O, Honkela A, Aittokallio T, Wennerberg K; NCI DREAM Community, Collins JJ, Gallahan D, Singer D, Saez-Rodriguez J, Kaski S, Gray JW, Stolovitzky G.

Nat Biotechnol. 2014 Dec;32(12):1202-12. doi: 10.1038/nbt.2877. Epub 2014 Jun 1.

28.

Exploration and retrieval of whole-metagenome sequencing samples.

Seth S, Välimäki N, Kaski S, Honkela A.

Bioinformatics. 2014 Sep 1;30(17):2471-9. doi: 10.1093/bioinformatics/btu340. Epub 2014 May 19.

29.

Probabilistic drug connectivity mapping.

Parkkinen JA, Kaski S.

BMC Bioinformatics. 2014 Apr 17;15:113. doi: 10.1186/1471-2105-15-113.

30.

Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression.

Marttinen P, Pirinen M, Sarin AP, Gillberg J, Kettunen J, Surakka I, Kangas AJ, Soininen P, O'Reilly P, Kaakinen M, Kähönen M, Lehtimäki T, Ala-Korpela M, Raitakari OT, Salomaa V, Järvelin MR, Ripatti S, Kaski S.

Bioinformatics. 2014 Jul 15;30(14):2026-34. doi: 10.1093/bioinformatics/btu140. Epub 2014 Mar 24.

31.

Genome-wide association studies with high-dimensional phenotypes.

Marttinen P, Gillberg J, Havulinna A, Corander J, Kaski S.

Stat Appl Genet Mol Biol. 2013 Aug;12(4):413-31. doi: 10.1515/sagmb-2012-0032.

PMID:
23759510
32.

Targeted retrieval of gene expression measurements using regulatory models.

Georgii E, Salojärvi J, Brosché M, Kangasjärvi J, Kaski S.

Bioinformatics. 2012 Sep 15;28(18):2349-56. Epub 2012 Jun 27.

PMID:
22743225
33.

Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs.

Khan SA, Faisal A, Mpindi JP, Parkkinen JA, Kalliokoski T, Poso A, Kallioniemi OP, Wennerberg K, Kaski S.

BMC Bioinformatics. 2012 May 30;13:112. doi: 10.1186/1471-2105-13-112.

34.

The rocky road to personalized medicine: computational and statistical challenges.

Corander J, Aittokallio T, Ripatti S, Kaski S.

Per Med. 2012 Mar;9(2):109-114. doi: 10.2217/pme.12.1. No abstract available.

PMID:
29758814
35.

Identifying fragments of natural speech from the listener's MEG signals.

Koskinen M, Viinikanoja J, Kurimo M, Klami A, Kaski S, Hari R.

Hum Brain Mapp. 2013 Jun;34(6):1477-89. doi: 10.1002/hbm.22004. Epub 2012 Feb 17.

PMID:
22344824
36.

Data-driven information retrieval in heterogeneous collections of transcriptomics data links SIM2s to malignant pleural mesothelioma.

Caldas J, Gehlenborg N, Kettunen E, Faisal A, Rönty M, Nicholson AG, Knuutila S, Brazma A, Kaski S.

Bioinformatics. 2012 Jan 15;28(2):246-53. doi: 10.1093/bioinformatics/btr634. Epub 2011 Nov 20.

37.

Metabolic regulation in progression to autoimmune diabetes.

Sysi-Aho M, Ermolov A, Gopalacharyulu PV, Tripathi A, Seppänen-Laakso T, Maukonen J, Mattila I, Ruohonen ST, Vähätalo L, Yetukuri L, Härkönen T, Lindfors E, Nikkilä J, Ilonen J, Simell O, Saarela M, Knip M, Kaski S, Savontaus E, Orešič M.

PLoS Comput Biol. 2011 Oct;7(10):e1002257. doi: 10.1371/journal.pcbi.1002257. Epub 2011 Oct 27.

38.

High density lipoprotein structural changes and drug response in lipidomic profiles following the long-term fenofibrate therapy in the FIELD substudy.

Yetukuri L, Huopaniemi I, Koivuniemi A, Maranghi M, Hiukka A, Nygren H, Kaski S, Taskinen MR, Vattulainen I, Jauhiainen M, Orešič M.

PLoS One. 2011;6(8):e23589. doi: 10.1371/journal.pone.0023589. Epub 2011 Aug 24.

39.

Hierarchical generative biclustering for microRNA expression analysis.

Caldas J, Kaski S.

J Comput Biol. 2011 Mar;18(3):251-61. doi: 10.1089/cmb.2010.0256.

PMID:
21385032
40.

Probabilistic analysis of probe reliability in differential gene expression studies with short oligonucleotide arrays.

Lahti L, Elo LL, Aittokallio T, Kaski S.

IEEE/ACM Trans Comput Biol Bioinform. 2011 Jan-Mar;8(1):217-25. doi: 10.1109/TCBB.2009.38.

PMID:
21071809
41.

Global modeling of transcriptional responses in interaction networks.

Lahti L, Knuuttila JE, Kaski S.

Bioinformatics. 2010 Nov 1;26(21):2713-20. doi: 10.1093/bioinformatics/btq500. Epub 2010 Sep 2.

PMID:
20813878
42.

Multivariate multi-way analysis of multi-source data.

Huopaniemi I, Suvitaival T, Nikkilä J, Oresic M, Kaski S.

Bioinformatics. 2010 Jun 15;26(12):i391-8. doi: 10.1093/bioinformatics/btq174.

43.

Searching for functional gene modules with interaction component models.

Parkkinen JA, Kaski S.

BMC Syst Biol. 2010 Jan 25;4:4. doi: 10.1186/1752-0509-4-4.

44.

Probabilistic retrieval and visualization of biologically relevant microarray experiments.

Caldas J, Gehlenborg N, Faisal A, Brazma A, Kaski S.

Bioinformatics. 2009 Jun 15;25(12):i145-53. doi: 10.1093/bioinformatics/btp215.

45.

Evolutionary conservation of orthoretroviral long terminal repeats (LTRs) and ab initio detection of single LTRs in genomic data.

Benachenhou F, Jern P, Oja M, Sperber G, Blikstad V, Somervuo P, Kaski S, Blomberg J.

PLoS One. 2009;4(4):e5179. doi: 10.1371/journal.pone.0005179. Epub 2009 Apr 13.

46.

Dependencies between stimuli and spatially independent fMRI sources: towards brain correlates of natural stimuli.

Ylipaavalniemi J, Savia E, Malinen S, Hari R, Vigário R, Kaski S.

Neuroimage. 2009 Oct 15;48(1):176-85. doi: 10.1016/j.neuroimage.2009.03.056. Epub 2009 Apr 1.

PMID:
19344775
47.

Combined use of expression and CGH arrays pinpoints novel candidate genes in Ewing sarcoma family of tumors.

Savola S, Klami A, Tripathi A, Niini T, Serra M, Picci P, Kaski S, Zambelli D, Scotlandi K, Knuutila S.

BMC Cancer. 2009 Jan 14;9:17. doi: 10.1186/1471-2407-9-17.

48.

Gender-dependent progression of systemic metabolic states in early childhood.

Nikkilä J, Sysi-Aho M, Ermolov A, Seppänen-Laakso T, Simell O, Kaski S, Oresic M.

Mol Syst Biol. 2008;4:197. doi: 10.1038/msb.2008.34. Epub 2008 Jun 3.

49.

Simple integrative preprocessing preserves what is shared in data sources.

Tripathi A, Klami A, Kaski S.

BMC Bioinformatics. 2008 Feb 21;9:111. doi: 10.1186/1471-2105-9-111.

50.

Bankruptcy analysis with self-organizing maps in learning metrics.

Kaski S, Sinkkonen J, Peltonen J.

IEEE Trans Neural Netw. 2001;12(4):936-47. doi: 10.1109/72.935102.

PMID:
18249924

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