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Items: 1 to 50 of 167

1.

Adrenals Contribute to Growth of Castration-Resistant VCaP Prostate Cancer Xenografts.

Huhtaniemi R, Oksala R, Knuuttila M, Mehmood A, Aho E, Laajala TD, Nicorici D, Aittokallio T, Laiho A, Elo L, Ohlsson C, Kallio P, Mäkelä S, Mustonen MVJ, Sipilä P, Poutanen M.

Am J Pathol. 2018 Sep 28. pii: S0002-9440(18)30499-1. doi: 10.1016/j.ajpath.2018.07.029. [Epub ahead of print]

PMID:
30273606
2.

Drug Target Commons 2.0: a community platform for systematic analysis of drug-target interaction profiles.

Tanoli Z, Alam Z, Vähä-Koskela M, Ravikumar B, Malyutina A, Jaiswal A, Tang J, Wennerberg K, Aittokallio T.

Database (Oxford). 2018 Jan 1;2018:1-13. doi: 10.1093/database/bay083.

3.

Machine learning and feature selection for drug response prediction in precision oncology applications.

Ali M, Aittokallio T.

Biophys Rev. 2018 Aug 10. doi: 10.1007/s12551-018-0446-z. [Epub ahead of print] Review.

4.

PP2A inhibition is a druggable MEK inhibitor resistance mechanism in KRAS-mutant lung cancer cells.

Kauko O, O'Connor CM, Kulesskiy E, Sangodkar J, Aakula A, Izadmehr S, Yetukuri L, Yadav B, Padzik A, Laajala TD, Haapaniemi P, Momeny M, Varila T, Ohlmeyer M, Aittokallio T, Wennerberg K, Narla G, Westermarck J.

Sci Transl Med. 2018 Jul 18;10(450). pii: eaaq1093. doi: 10.1126/scitranslmed.aaq1093.

PMID:
30021885
5.

Corrigendum to "Searching for drug synergy in complex dose-response landscapes using an interaction potency model" [Comput. Struct. Biotechnol. J. 13 (2015) 504-513].

Yadav B, Wennerberg K, Aittokallio T, Tang J.

Comput Struct Biotechnol J. 2017 Jul 25;15:387. doi: 10.1016/j.csbj.2017.07.003. eCollection 2017.

6.

Susceptibility of low-density lipoprotein particles to aggregate depends on particle lipidome, is modifiable, and associates with future cardiovascular deaths.

Ruuth M, Nguyen SD, Vihervaara T, Hilvo M, Laajala TD, Kondadi PK, Gisterå A, Lähteenmäki H, Kittilä T, Huusko J, Uusitupa M, Schwab U, Savolainen MJ, Sinisalo J, Lokki ML, Nieminen MS, Jula A, Perola M, Ylä-Herttula S, Rudel L, Öörni A, Baumann M, Baruch A, Laaksonen R, Ketelhuth DFJ, Aittokallio T, Jauhiainen M, Käkelä R, Borén J, Williams KJ, Kovanen PT, Öörni K.

Eur Heart J. 2018 Jul 14;39(27):2562-2573. doi: 10.1093/eurheartj/ehy319.

7.

Drug-Sensitivity Screening and Genomic Characterization of 45 HPV-Negative Head and Neck Carcinoma Cell Lines for Novel Biomarkers of Drug Efficacy.

Lepikhova T, Karhemo PR, Louhimo R, Yadav B, Murumägi A, Kulesskiy E, Kivento M, Sihto H, Grénman R, Syrjänen SM, Kallioniemi O, Aittokallio T, Wennerberg K, Joensuu H, Monni O.

Mol Cancer Ther. 2018 Sep;17(9):2060-2071. doi: 10.1158/1535-7163.MCT-17-0733. Epub 2018 Jul 3.

PMID:
29970484
8.

Learning with multiple pairwise kernels for drug bioactivity prediction.

Cichonska A, Pahikkala T, Szedmak S, Julkunen H, Airola A, Heinonen M, Aittokallio T, Rousu J.

Bioinformatics. 2018 Jul 1;34(13):i509-i518. doi: 10.1093/bioinformatics/bty277.

9.

Immune cell contexture in the bone marrow tumor microenvironment impacts therapy response in CML.

Brück O, Blom S, Dufva O, Turkki R, Chheda H, Ribeiro A, Kovanen P, Aittokallio T, Koskenvesa P, Kallioniemi O, Porkka K, Pellinen T, Mustjoki S.

Leukemia. 2018 Jul;32(7):1643-1656. doi: 10.1038/s41375-018-0175-0. Epub 2018 Jun 20.

PMID:
29925907
10.

ePCR: an R-package for survival and time-to-event prediction in advanced prostate cancer, applied to real-world patient cohorts.

Laajala TD, Murtojärvi M, Virkki A, Aittokallio T.

Bioinformatics. 2018 Nov 15;34(22):3957-3959. doi: 10.1093/bioinformatics/bty477.

PMID:
29912284
11.

Novel activities of safe-in-human broad-spectrum antiviral agents.

Ianevski A, Zusinaite E, Kuivanen S, Strand M, Lysvand H, Teppor M, Kakkola L, Paavilainen H, Laajala M, Kallio-Kokko H, Valkonen M, Kantele A, Telling K, Lutsar I, Letjuka P, Metelitsa N, Oksenych V, Bjørås M, Nordbø SA, Dumpis U, Vitkauskiene A, Öhrmalm C, Bondeson K, Bergqvist A, Aittokallio T, Cox RJ, Evander M, Hukkanen V, Marjomaki V, Julkunen I, Vapalahti O, Tenson T, Merits A, Kainov D.

Antiviral Res. 2018 Jun;154:174-182. doi: 10.1016/j.antiviral.2018.04.016. Epub 2018 Apr 23.

PMID:
29698664
12.

Aggressive natural killer-cell leukemia mutational landscape and drug profiling highlight JAK-STAT signaling as therapeutic target.

Dufva O, Kankainen M, Kelkka T, Sekiguchi N, Awad SA, Eldfors S, Yadav B, Kuusanmäki H, Malani D, Andersson EI, Pietarinen P, Saikko L, Kovanen PE, Ojala T, Lee DA, Loughran TP Jr, Nakazawa H, Suzumiya J, Suzuki R, Ko YH, Kim WS, Chuang SS, Aittokallio T, Chan WC, Ohshima K, Ishida F, Mustjoki S.

Nat Commun. 2018 Apr 19;9(1):1567. doi: 10.1038/s41467-018-03987-2.

13.

Combined ASRGL1 and p53 immunohistochemistry as an independent predictor of survival in endometrioid endometrial carcinoma.

Huvila J, Laajala TD, Edqvist PH, Mardinoglu A, Talve L, Pontén F, Grénman S, Carpén O, Aittokallio T, Auranen A.

Gynecol Oncol. 2018 Apr;149(1):173-180. doi: 10.1016/j.ygyno.2018.02.016. Epub 2018 Mar 2.

PMID:
29486992
14.

Patient-Customized Drug Combination Prediction and Testing for T-cell Prolymphocytic Leukemia Patients.

He L, Tang J, Andersson EI, Timonen S, Koschmieder S, Wennerberg K, Mustjoki S, Aittokallio T.

Cancer Res. 2018 May 1;78(9):2407-2418. doi: 10.1158/0008-5472.CAN-17-3644. Epub 2018 Feb 26.

PMID:
29483097
15.

Secreted frizzled-related protein 2 (SFRP2) expression promotes lesion proliferation via canonical WNT signaling and indicates lesion borders in extraovarian endometriosis.

Heinosalo T, Gabriel M, Kallio L, Adhikari P, Huhtinen K, Laajala TD, Kaikkonen E, Mehmood A, Suvitie P, Kujari H, Aittokallio T, Perheentupa A, Poutanen M.

Hum Reprod. 2018 May 1;33(5):817-831. doi: 10.1093/humrep/dey026.

PMID:
29462326
16.

Methods for High-throughput Drug Combination Screening and Synergy Scoring.

He L, Kulesskiy E, Saarela J, Turunen L, Wennerberg K, Aittokallio T, Tang J.

Methods Mol Biol. 2018;1711:351-398. doi: 10.1007/978-1-4939-7493-1_17.

PMID:
29344898
17.

Drug Target Commons: A Community Effort to Build a Consensus Knowledge Base for Drug-Target Interactions.

Tang J, Tanoli ZU, Ravikumar B, Alam Z, Rebane A, Vähä-Koskela M, Peddinti G, van Adrichem AJ, Wakkinen J, Jaiswal A, Karjalainen E, Gautam P, He L, Parri E, Khan S, Gupta A, Ali M, Yetukuri L, Gustavsson AL, Seashore-Ludlow B, Hersey A, Leach AR, Overington JP, Repasky G, Wennerberg K, Aittokallio T.

Cell Chem Biol. 2018 Feb 15;25(2):224-229.e2. doi: 10.1016/j.chembiol.2017.11.009. Epub 2017 Dec 21.

18.

Improving the efficacy-safety balance of polypharmacology in multi-target drug discovery.

Ravikumar B, Aittokallio T.

Expert Opin Drug Discov. 2018 Feb;13(2):179-192. doi: 10.1080/17460441.2018.1413089. Epub 2017 Dec 12.

PMID:
29233023
19.

Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach.

Ali M, Khan SA, Wennerberg K, Aittokallio T.

Bioinformatics. 2018 Apr 15;34(8):1353-1362. doi: 10.1093/bioinformatics/btx766.

20.

Antiandrogens Reduce Intratumoral Androgen Concentrations and Induce Androgen Receptor Expression in Castration-Resistant Prostate Cancer Xenografts.

Knuuttila M, Mehmood A, Huhtaniemi R, Yatkin E, Häkkinen MR, Oksala R, Laajala TD, Ryberg H, Handelsman DJ, Aittokallio T, Auriola S, Ohlsson C, Laiho A, Elo LL, Sipilä P, Mäkelä SI, Poutanen M.

Am J Pathol. 2018 Jan;188(1):216-228. doi: 10.1016/j.ajpath.2017.08.036. Epub 2017 Nov 7.

PMID:
29126837
21.

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
22.

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
23.

Antiviral Properties of Chemical Inhibitors of Cellular Anti-Apoptotic Bcl-2 Proteins.

Bulanova D, Ianevski A, Bugai A, Akimov Y, Kuivanen S, Paavilainen H, Kakkola L, Nandania J, Turunen L, Ohman T, Ala-Hongisto H, Pesonen HM, Kuisma MS, Honkimaa A, Walton EL, Oksenych V, Lorey MB, Guschin D, Shim J, Kim J, Than TT, Chang SY, Hukkanen V, Kulesskiy E, Marjomaki VS, Julkunen I, Nyman TA, Matikainen S, Saarela JS, Sane F, Hober D, Gabriel G, De Brabander JK, Martikainen M, Windisch MP, Min JY, Bruzzone R, Aittokallio T, Vähä-Koskela M, Vapalahti O, Pulk A, Velagapudi V, Kainov DE.

Viruses. 2017 Sep 25;9(10). pii: E271. doi: 10.3390/v9100271.

24.

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.

25.

In Search of System-Wide Productivity Gains - The Role of Global Collaborations in Preclinical Translation.

Ussi AE, de Kort M, Coussens NP, Aittokallio T, Hajduch M.

Clin Transl Sci. 2017 Nov;10(6):423-425. doi: 10.1111/cts.12498. Epub 2017 Sep 19. No abstract available.

PMID:
28929592
26.

Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression.

Ammad-Ud-Din M, Khan SA, Wennerberg K, Aittokallio T.

Bioinformatics. 2017 Jul 15;33(14):i359-i368. doi: 10.1093/bioinformatics/btx266.

27.

Discovery of novel drug sensitivities in T-PLL by high-throughput ex vivo drug testing and mutation profiling.

Andersson EI, Pützer S, Yadav B, Dufva O, Khan S, He L, Sellner L, Schrader A, Crispatzu G, Oleś M, Zhang H, Adnan-Awad S, Lagström S, Bellanger D, Mpindi JP, Eldfors S, Pemovska T, Pietarinen P, Lauhio A, Tomska K, Cuesta-Mateos C, Faber E, Koschmieder S, Brümmendorf TH, Kytölä S, Savolainen ER, Siitonen T, Ellonen P, Kallioniemi O, Wennerberg K, Ding W, Stern MH, Huber W, Anders S, Tang J, Aittokallio T, Zenz T, Herling M, Mustjoki S.

Leukemia. 2018 Mar;32(3):774-787. doi: 10.1038/leu.2017.252. Epub 2017 Aug 14.

PMID:
28804127
28.

Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors.

Cichonska A, Ravikumar B, Parri E, Timonen S, Pahikkala T, Airola A, Wennerberg K, Rousu J, Aittokallio T.

PLoS Comput Biol. 2017 Aug 7;13(8):e1005678. doi: 10.1371/journal.pcbi.1005678. eCollection 2017 Aug.

29.

JAK1/2 and BCL2 inhibitors synergize to counteract bone marrow stromal cell-induced protection of AML.

Karjalainen R, Pemovska T, Popa M, Liu M, Javarappa KK, Majumder MM, Yadav B, Tamborero D, Tang J, Bychkov D, Kontro M, Parsons A, Suvela M, Mayoral Safont M, Porkka K, Aittokallio T, Kallioniemi O, McCormack E, Gjertsen BT, Wennerberg K, Knowles J, Heckman CA.

Blood. 2017 Aug 10;130(6):789-802. doi: 10.1182/blood-2016-02-699363. Epub 2017 Jun 15.

30.

Early metabolic markers identify potential targets for the prevention of type 2 diabetes.

Peddinti G, Cobb J, Yengo L, Froguel P, Kravić J, Balkau B, Tuomi T, Aittokallio T, Groop L.

Diabetologia. 2017 Sep;60(9):1740-1750. doi: 10.1007/s00125-017-4325-0. Epub 2017 Jun 8.

31.

Seed-effect modeling improves the consistency of genome-wide loss-of-function screens and identifies synthetic lethal vulnerabilities in cancer cells.

Jaiswal A, Peddinti G, Akimov Y, Wennerberg K, Kuznetsov S, Tang J, Aittokallio T.

Genome Med. 2017 Jun 1;9(1):51. doi: 10.1186/s13073-017-0440-2.

32.

Rapalogs can promote cancer cell stemness in vitro in a Galectin-1 and H-ras-dependent manner.

Posada IMD, Lectez B, Sharma M, Oetken-Lindholm C, Yetukuri L, Zhou Y, Aittokallio T, Abankwa D.

Oncotarget. 2017 Jul 4;8(27):44550-44566. doi: 10.18632/oncotarget.17819.

33.
34.

Matched preclinical designs for improved translatability.

Aittokallio T, Scherer A, Poutanen M, Freedman LP.

Sci Transl Med. 2017 May 10;9(389). pii: eaal4101. doi: 10.1126/scitranslmed.aal4101.

PMID:
28490671
35.

C-SPADE: a web-tool for interactive analysis and visualization of drug screening experiments through compound-specific bioactivity dendrograms.

Ravikumar B, Alam Z, Peddinti G, Aittokallio T.

Nucleic Acids Res. 2017 Jul 3;45(W1):W495-W500. doi: 10.1093/nar/gkx384.

36.

SynergyFinder: a web application for analyzing drug combination dose-response matrix data.

Ianevski A, He L, Aittokallio T, Tang J.

Bioinformatics. 2017 Aug 1;33(15):2413-2415. doi: 10.1093/bioinformatics/btx162.

37.

Whole-genome view of the consequences of a population bottleneck using 2926 genome sequences from Finland and United Kingdom.

Chheda H, Palta P, Pirinen M, McCarthy S, Walter K, Koskinen S, Salomaa V, Daly M, Durbin R, Palotie A, Aittokallio T, Ripatti S.

Eur J Hum Genet. 2017 Apr;25(4):477-484. doi: 10.1038/ejhg.2016.205. Epub 2017 Feb 1.

38.

Systematic drug sensitivity testing reveals synergistic growth inhibition by dasatinib or mTOR inhibitors with paclitaxel in ovarian granulosa cell tumor cells.

Haltia UM, Andersson N, Yadav B, Färkkilä A, Kulesskiy E, Kankainen M, Tang J, Bützow R, Riska A, Leminen A, Heikinheimo M, Kallioniemi O, Unkila-Kallio L, Wennerberg K, Aittokallio T, Anttonen M.

Gynecol Oncol. 2017 Mar;144(3):621-630. doi: 10.1016/j.ygyno.2016.12.016. Epub 2017 Jan 16.

PMID:
28104295
39.

Consistency in drug response profiling.

Mpindi JP, Yadav B, Östling P, Gautam P, Malani D, Murumägi A, Hirasawa A, Kangaspeska S, Wennerberg K, Kallioniemi O, Aittokallio T.

Nature. 2016 Nov 30;540(7631):E5-E6. doi: 10.1038/nature20171. No abstract available.

PMID:
27905421
40.

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.

Guinney J, Wang T, Laajala TD, Winner KK, Bare JC, Neto EC, Khan SA, Peddinti G, Airola A, Pahikkala T, Mirtti T, Yu T, Bot BM, Shen L, Abdallah K, Norman T, Friend S, Stolovitzky G, Soule H, Sweeney CJ, Ryan CJ, Scher HI, Sartor O, Xie Y, Aittokallio T, Zhou FL, Costello JC; Prostate Cancer Challenge DREAM Community.

Lancet Oncol. 2017 Jan;18(1):132-142. doi: 10.1016/S1470-2045(16)30560-5. Epub 2016 Nov 16.

41.

Enhanced sensitivity to glucocorticoids in cytarabine-resistant AML.

Malani D, Murumägi A, Yadav B, Kontro M, Eldfors S, Kumar A, Karjalainen R, Majumder MM, Ojamies P, Pemovska T, Wennerberg K, Heckman C, Porkka K, Wolf M, Aittokallio T, Kallioniemi O.

Leukemia. 2017 May;31(5):1187-1195. doi: 10.1038/leu.2016.314. Epub 2016 Nov 11.

42.

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.

43.

Orphan G protein-coupled receptor GPRC5A modulates integrin β1-mediated epithelial cell adhesion.

Bulanova DR, Akimov YA, Rokka A, Laajala TD, Aittokallio T, Kouvonen P, Pellinen T, Kuznetsov SG.

Cell Adh Migr. 2017 Sep 3;11(5-6):434-446. doi: 10.1080/19336918.2016.1245264. Epub 2017 Feb 6.

44.

Multi-Omics Studies towards Novel Modulators of Influenza A Virus-Host Interaction.

Söderholm S, Fu Y, Gaelings L, Belanov S, Yetukuri L, Berlinkov M, Cheltsov AV, Anders S, Aittokallio T, Nyman TA, Matikainen S, Kainov DE.

Viruses. 2016 Sep 29;8(10). pii: E269. Review.

45.

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
46.

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.

47.

The Hydroxysteroid (17β) Dehydrogenase Family Gene HSD17B12 Is Involved in the Prostaglandin Synthesis Pathway, the Ovarian Function, and Regulation of Fertility.

Kemiläinen H, Adam M, Mäki-Jouppila J, Damdimopoulou P, Damdimopoulos AE, Kere J, Hovatta O, Laajala TD, Aittokallio T, Adamski J, Ryberg H, Ohlsson C, Strauss L, Poutanen M.

Endocrinology. 2016 Oct;157(10):3719-3730. Epub 2016 Aug 4.

PMID:
27490311
48.

Phosphoproteomics to Characterize Host Response During Influenza A Virus Infection of Human Macrophages.

Söderholm S, Kainov DE, Öhman T, Denisova OV, Schepens B, Kulesskiy E, Imanishi SY, Corthals G, Hintsanen P, Aittokallio T, Saelens X, Matikainen S, Nyman TA.

Mol Cell Proteomics. 2016 Oct;15(10):3203-3219. Epub 2016 Aug 2.

49.

Optimized design and analysis of preclinical intervention studies in vivo.

Laajala TD, Jumppanen M, Huhtaniemi R, Fey V, Kaur A, Knuuttila M, Aho E, Oksala R, Westermarck J, Mäkelä S, Poutanen M, Aittokallio T.

Sci Rep. 2016 Aug 2;6:30723. doi: 10.1038/srep30723.

50.

Systematic drug screening reveals specific vulnerabilities and co-resistance patterns in endocrine-resistant breast cancer.

Kangaspeska S, Hultsch S, Jaiswal A, Edgren H, Mpindi JP, Eldfors S, Brück O, Aittokallio T, Kallioniemi O.

BMC Cancer. 2016 Jul 4;16:378. doi: 10.1186/s12885-016-2452-5.

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