Yudi Pawitan
Professor
E-mail: yudi.pawitan@ki.se
Visiting address: Nobels väg 12a, 17165 Solna
Postal address: C8 Medicinsk epidemiologi och biostatistik, C8 MEB Pawitan, 171 77 Stockholm
About me
Education
- 1982 BSc in Statistics from Bogor Agriculture Institute, Indonesia
- 1984 MSc in Statistics from University of California at Davis
- 1987 PhD in Statistics from University of California at Davis
Research
I work mostly in the development of statistical methods for analyses of high-throughput data as currently generated in genomic studies, including SNP and RNA arrays, and next-generation sequencing.
Articles
- Article: NUCLEIC ACIDS RESEARCH. 2025;53(14):gkaf714Wang Q; Khatri P; Dinh HQ; Huang J; Pawitan Y; Vu TN
- Article: NATURE GENETICS. 2025;57(4):1053-1058Li Y; Pawitan Y; Shen X
- Article: PHARMACEUTICAL STATISTICS. 2024;23(6):1117-1127Kim H; Jung S; Pawitan Y; Lee W
- Article: ANNALS OF NEUROLOGY. 2024;96(4):694-703Hu Y; Frisell T; Alping P; Song H; Pawitan Y; Fang F; Piehl F
- Article: EJHAEM. 2024;5(4):721-727Caliskan G; Pawitan Y; Vu TN
- Article: SCANDINAVIAN JOURNAL OF STATISTICS. 2023;50(4):1859-1883Pawitan Y; Lee H; Lee Y
- Article: EUROPEAN JOURNAL OF NEUROLOGY. 2023;30(11):3430-3439Sun J; Ludvigsson JF; Roelstraete B; Pedersen NL; Pawitan Y; Wirdefeldt K; Fang F
- Journal article: PHENOMICS. 2023;:1Pan L; Zheng C; Yang Z; Pawitan Y; Vu TN; Shen X
- Article: ECLINICALMEDICINE. 2023;61:102063Shen Q; Mikkelsen DH; Luitva LB; Song H; Kasela S; Aspelund T; Bergstedt J; Lu Y; Sullivan PF; Ye W; Fall K; Tornvall P; Pawitan Y; Andreassen OA; Buil A; Milani L; Fang F; Valdimarsdottir U
- Article: PHENOMICS. 2023;3(3):217-227Pan L; Zheng C; Yang Z; Pawitan Y; Vu TN; Shen X
- Article: CANCER MEDICINE. 2023;12(8):10156-10168Silvestri M; Vu TN; Nichetti F; Niger M; Di Cosimo S; De Braud F; Pruneri G; Pawitan Y; Calza S; Cappelletti V
- Article: NPJ PRECISION ONCOLOGY. 2023;7(1):32Trac QT; Pawitan Y; Mou T; Erkers T; Ostling P; Bohlin A; Osterroos A; Vesterlund M; Jafari R; Siavelis I; Backvall H; Kiviluoto S; Orre LM; Rantalainen M; Lehtio J; Lehmann S; Kallioniemi O; Vu TN
- Article: BRAIN COMMUNICATIONS. 2023;5(2):fcad065Hu Y; Hu K; Song H; Pawitan Y; Piehl F; Fang F
- Article: STATISTICS IN MEDICINE. 2022;41(30):5830-5843Lee W; Lee D; Pawitan Y
- Article: NATURE COMMUNICATIONS. 2022;13(1):6733Yazdani S; Seitz C; Cui C; Lovik A; Pan L; Piehl F; Pawitan Y; Klappe U; Press R; Samuelsson K; Yin L; Vu TN; Joly A-L; Westerberg LS; Evertsson B; Ingre C; Andersson J; Fang F
- Article: HUMAN MOLECULAR GENETICS. 2022;31(21):3643-3651Zhai R; Pan L; Yang Z; Li T; Ning Z; Pawitan Y; Wilson JF; Wu D; Shen X
- Article: GIGASCIENCE. 2022;11:giac091Quang TT; Zhou T; Pawitan Y; Trung NV
- Article: NAR GENOMICS AND BIOINFORMATICS. 2022;4(3):lqac052Deng W; Mou T; Pawitan Y; Trung NV
- Article: CIRCULATION. 2022;145(18):1398-1411Yang Z; Macdonald-Dunlop E; Chen J; Zhai R; Li T; Richmond A; Klaric L; Pirastu N; Ning Z; Zheng C; Wang Y; Huang T; He Y; Guo H; Ying K; Gustafsson S; Prins B; Ramisch A; Dermitzakis ET; Png G; Eriksson N; Haessler J; Hu X; Zanetti D; Boutin T; Hwang S-J; Wheeler E; Pietzner M; Raffield LM; Kalnapenkis A; Peters JE; Vinuela A; Gilly A; Elmstahl S; Dedoussis G; Petrie JR; Polasek O; Folkersen L; Chen Y; Yao C; Vosa U; Pairo-Castineira E; Clohisey S; Bretherick AD; Rawlik K; Esko T; Enroth S; Johansson A; Gyllensten U; Langenberg C; Levy D; Hayward C; Assimes TL; Kooperberg C; Manichaikul AW; Siegbahn A; Wallentin L; Lind L; Zeggini E; Schwenk JM; Butterworth AS; Michaelsson K; Pawitan Y; Joshi PK; Baillie JK; Malarstig A; Reiner AP; Wilson JF; Shen X
- Article: FRONTIERS IN GENETICS. 2022;13:798269Yang Z; Xu W; Zhai R; Li T; Ning Z; Pawitan Y; Shen X
- Article: ELIFE. 2022;11:e74065Cui C; Ingre C; Yin L; Li X; Andersson J; Seitz C; Ruffin N; Pawitan Y; Piehl F; Fang F
- Article: FRONTIERS IN GENETICS. 2022;13:820493Deng W; Murugan S; Lindberg J; Chellappa V; Shen X; Pawitan Y; Vu TN
- Article: BIOINFORMATICS. 2022;38(5):1287-1294Pan L; Dinh HQ; Pawitan Y; Trung NV
- Article: PHENOMICS. 2022;2(3):184-193Yang H; Pawitan Y; Fang F; Czene K; Ye W
- Article: JOURNAL OF INTERNAL MEDICINE. 2022;291(1):95-100Dahlen T; Zhao J; Magnusson PKE; Pawitan Y; Lavrod J; Edgren G
- Article: BMC BIOINFORMATICS. 2021;22(1):495Nguyen DT; Trac QT; Nguyen T-H; Nguyen H-N; Ohad N; Pawitan Y; Vu TN
- Article: AMYOTROPHIC LATERAL SCLEROSIS AND FRONTOTEMPORAL DEGENERATION. 2021;22(5-6):410-418Sun J; Ludvigsson JF; Roelstraete B; Pawitan Y; Fang F
- Article: AMERICAN JOURNAL OF HEMATOLOGY. 2021;96(5):580-588Mou T; Pawitan Y; Stahl M; Vesterlund M; Deng W; Jafari R; Bohlin A; Osterroos A; Siavelis L; Backvall H; Erkers T; Kiviluoto S; Seashore-Ludlow B; Ostling P; Orre LM; Kallioniemi O; Lehmann S; Lehtio J; Trung NV
- Journal article: NEUROLOGY. 2021;96(15_supplement)Cui C; Sun J; Pawitan Y; Piehl F; Chen H; Ingre C; Wirdefeldt K; Evans M; Andersson J; Carrero J-J; Fang F
- Journal article: NEUROLOGY. 2021;96(15_supplement)sun J; Ludvigsson J; Roelstraete B; pawitan Y; Fang F
- Article: AMYOTROPHIC LATERAL SCLEROSIS AND FRONTOTEMPORAL DEGENERATION. 2021;22(3-4):211-219Cui C; Longinetti E; Larsson H; Andersson J; Pawitan Y; Piehl F; Fang F
- Article: FRONTIERS IN GENETICS. 2021;12:627989Ning Z; Tsepilov YA; Sharapov SZ; Wang Z; Grishenko AK; Feng X; Shirali M; Joshi PK; Wilson JF; Pawitan Y; Haley CS; Aulchenko YS; Shen X
- Article: EUROPEAN JOURNAL OF NEUROLOGY. 2020;27(11):2125-2133Sun J; Carrero JJ; Zagai U; Evans M; Ingre C; Pawitan Y; Fang F
- Article: SCIENTIFIC REPORTS. 2020;10(1):18392Grassmann F; Pawitan Y; Czene K
- Article: LIFE SCIENCE ALLIANCE. 2020;3(10):e202000817Hong M-G; Dodig-Crnkovic T; Chen X; Drobin K; Lee W; Wang Y; Edfors F; Kotol D; Thomas CE; Sjoberg R; Odeberg J; Hamsten A; Silveira A; Hall P; Nilsson P; Pawitan Y; Uhlen M; Pedersen NL; Hagg S; Magnusson PK; Schwenk JM
- Article: NATURE GENETICS. 2020;52(8):859-864Ning Z; Pawitan Y; Shen X
- Article: BRAIN COMMUNICATIONS. 2020;2(2):fcaa152Cui C; Sun J; Pawitan Y; Piehl F; Chen H; Ingre C; Wirdefeldt K; Evans M; Andersson J; Carrero J-J; Fang F
- Article: THEORY AND DECISION. 2020;88(4):595-607Pawitan Y; Isheden G
- Article: BIOINFORMATICS. 2020;36(3):805-812Deng W; Mou T; Kalari KR; Niu N; Wang L; Pawitan Y; Trung NV
- Article: FRONTIERS IN GENETICS. 2020;10:1331Mou T; Deng W; Gu F; Pawitan Y; Trung NV
- Article: EUROPEAN JOURNAL OF NEUROLOGY. 2019;26(11):1355-1361Sun J; Zhan Y; Mariosa D; Larsson H; Almqvist C; Ingre C; Zagai U; Pawitan Y; Fang F
- Article: BIOINFORMATICS. 2019;35(22):4679-4687Trung NV; Ha-Nam N; Calza S; Kalari KR; Wang L; Pawitan Y
- Article: BREAST CANCER RESEARCH. 2019;21(1):95Yang H; Pawitan Y; He W; Eriksson L; Holowko N; Hall P; Czene K
- Article: NATURE COMMUNICATIONS. 2019;10(1):2674Menden MP; Wang D; Mason MJ; Szalai B; Bulusu KC; Guan Y; Yu T; Kang J; Jeon M; Wolfinger R; Nguyen T; Zaslavskiy M; Jang IS; Ghazoui Z; Ahsen ME; Vogel R; Neto EC; Norman T; Tang EKY; Garnett MJ; Di Veroli GY; Fawell S; Stolovitzky G; Guinney J; Dry JR; Saez-Rodriguez J; Abante J; Abecassis BS; Aben N; Aghamirzaie D; Aittokallio T; Akhtari FS; Al-lazikani B; Alam T; Allam A; Allen C; de Almeida MP; Altarawy D; Alves V; Amadoz A; Anchang B; Antolin AA; Ash JR; Romeo Aznar V; Ba-alawi W; Bagheri M; Bajic V; Ball G; Ballester PJ; Baptista D; Bare C; Bateson M; Bender A; Bertrand D; Wijayawardena B; Boroevich KA; Bosdriesz E; Bougouffa S; Bounova G; Brouwer T; Bryant B; Calaza M; Calderone A; Calza S; Capuzzi S; Carbonell-Caballero J; Carlin D; Carter H; Castagnoli L; Celebi R; Cesareni G; Chang H; Chen G; Chen H; Chen H; Cheng L; Chernomoretz A; Chicco D; Cho K-H; Cho S; Choi D; Choi J; Choi K; Choi M; De Cock M; Coker E; Cortes-Ciriano I; Cserzo M; Cubuk C; Curtis C; Van Daele D; Dang CC; Dijkstra T; Dopazo J; Draghici S; Drosou A; Dumontier M; Ehrhart F; Eid F-E; ElHefnawi M; Elmarakeby H; van Engelen B; Engin HB; de Esch I; Evelo C; Falcao AO; Farag S; Fernandez-Lozano C; Fisch K; Flobak A; Fornari C; Foroushani ABK; Fotso DC; Fourches D; Friend S; Frigessi A; Gao F; Gao X; Gerold JM; Gestraud P; Ghosh S; Gillberg J; Godoy-Lorite A; Godynyuk L; Godzik A; Goldenberg A; Gomez-Cabrero D; Gonen M; de Graaf C; Gray H; Grechkin M; Guimera R; Guney E; Haibe-Kains B; Han Y; Hase T; He D; He L; Heath LS; Hellton KH; Helmer-Citterich M; Hidalgo MR; Hidru D; Hill SM; Hochreiter S; Hong S; Hovig E; Hsueh Y-C; Hu Z; Huang JK; Huang RS; Hunyady L; Hwang J; Hwang TH; Hwang W; Hwang Y; Isayev O; Walk OBD; Jack J; Jahandideh S; Ji J; Jo Y; Kamola PJ; Kanev GK; Karacosta L; Karimi M; Kaski S; Kazanov M; Khamis AM; Khan SA; Kiani NA; Kim A; Kim J; Kim J; Kim K; Kim K; Kim S; Kim Y; Kim Y; Kirk PDW; Kitano H; Klambauer G; Knowles D; Ko M; Kohn-Luque A; Kooistra AJ; Kuenemann MA; Kuiper M; Kurz C; Kwon M; van Laarhoven T; Laegreid A; Lederer S; Lee H; Lee J; Lee YW; Leppaho E; Lewis R; Li J; Li L; Liley J; Lim WK; Lin C; Liu Y; Lopez Y; Low J; Lysenko A; Machado D; Madhukar N; De Maeyer D; Malpartida AB; Mamitsuka H; Marabita F; Marchal K; Marttinen P; Mason D; Mazaheri A; Mehmood A; Mehreen A; Michaut M; Miller RA; Mitsopoulos C; Modos D; Van Moerbeke M; Moo K; Motsinger-Reif A; Movva R; Muraru S; Muratov E; Mushthofa M; Nagarajan N; Nakken S; Nath A; Neuvial P; Newton R; Ning Z; De Niz C; Oliva B; Olsen C; Palmeri A; Panesar B; Papadopoulos S; Park J; Park S; Park S; Pawitan Y; Peluso D; Pendyala S; Peng J; Perfetto L; Pirro S; Plevritis S; Politi R; Poon H; Porta E; Prellner I; Preuer K; Angel Pujana M; Ramnarine R; Reid JE; Reyal F; Richardson S; Ricketts C; Rieswijk L; Rocha M; Rodriguez-Gonzalvez C; Roell K; Rotroff D; de Ruiter JR; Rukawa P; Sadacca B; Safikhani Z; Safitri F; Sales-Pardo M; Sauer S; Schlichting M; Seoane JA; Serra J; Shang M-M; Sharma A; Sharma H; Shen Y; Shiga M; Shin M; Shkedy Z; Shopsowitz K; Sinai S; Skola D; Smirnov P; Soerensen IF; Soerensen P; Song J-H; Song SO; Soufan O; Spitzmueller A; Steipe B; Suphavilai C; Tamayo SP; Tamborero D; Tang J; Tanoli Z-U; Tarres-Deulofeu M; Tegner J; Thommesen L; Tonekaboni SAM; Tran H; De Troyer E; Truong A; Tsunoda T; Turu G; Tzeng G-Y; Verbeke L; Videla S; Vis D; Voronkov A; Votis K; Wang A; Wang H-QH; Wang P-W; Wang S; Wang W; Wang X; Wang X; Wennerberg K; Wernisch L; Wessels L; van Westen GJP; Westerman BA; White SR; Willighagen E; Wurdinger T; Xie L; Xie S; Xu H; Yadav B; Yau C; Yeerna H; Yin JW; Yu M; Yu M; Yun SJ; Zakharov A; Zamichos A; Zanin M; Zeng L; Zenil H; Zhang F; Zhang P; Zhang W; Zhao H; Zhao L; Zheng W; Zoufir A; Zucknick M
- Article: HUMAN GENETICS. 2019;138(4):425-435Dahlqwist E; Magnusson PKE; Pawitan Y; Sjolander A
- Article: SCIENTIFIC REPORTS. 2019;9(1):5064Hwang W; Calza S; Silvestri M; Pawitan Y; Lee Y
- Article: STATISTICAL METHODS IN MEDICAL RESEARCH. 2019;28(2):462-485Dahlqwist E; Pawitan Y; Sjolander A
- Article: STATISTICS IN MEDICINE. 2018;37(30):4695-4706Lee W; Sjolander A; Larsson A; Pawitan Y
- Article: BMC GENOMICS. 2018;19(1):786Trung NV; Deng W; Quang TT; Calza S; Hwang W; Pawitan Y
- Article: MOLECULAR ECOLOGY RESOURCES. 2018;18(6):1247-1262Wang M; Uebbing S; Pawitan Y; Scofield DG
- Article: COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2018;126:125-135Lee S; Lee Y; Pawitan Y
- Article: BIOLOGY DIRECT. 2018;13(1):14Suo C; Deng W; Trung NV; Li M; Shi L; Pawitan Y
- Article: BIOINFORMATICS. 2018;34(14):2392-2400Trung NV; Wills QF; Kalari KR; Niu N; Wang L; Pawitan Y; Rantalainen M
- Article: STATISTICAL METHODS IN MEDICAL RESEARCH. 2018;27(5):1531-1546Liu X-R; Pawitan Y; Clements M
- Article: BIOLOGICAL PSYCHIATRY. 2018;83(7):589-597Yip BHK; Bai D; Mahjani B; Klei L; Pawitan Y; Hultman CM; Grice DE; Roeder K; Buxbaum JD; Devlin B; Reichenberg A; Sandin S
- Article: STATISTICS IN MEDICINE. 2017;36(29):4743-4762Liu X-R; Pawitan Y; Clements MS
- Article: AMERICAN JOURNAL OF HUMAN GENETICS. 2017;101(6):903-912Ning Z; Lee Y; Joshi PK; Wilson JF; Pawitan Y; Shen X
- Article: STATISTICAL METHODS IN MEDICAL RESEARCH. 2017;26(5):2319-2332Lee S; Pawitan Y; Ingelsson E; Lee Y
- Article: AMERICAN STATISTICIAN. 2017;71(2):120-122Pawitan Y; Lee Y
- Article: BREAST CANCER RESEARCH. 2017;19(1):29Eriksson M; Czene K; Pawitan Y; Leifland K; Darabi H; Hall P
- Article: SCIENTIFIC REPORTS. 2017;7(1):67Setiawan A; Yin L; Auer G; Czene K; Smedby KE; Pawitan Y
- Article: ONCOTARGET. 2016;7(42):68851-68863Vu TN; Pramana S; Calza S; Suo C; Lee D; Pawitan Y
- Article: JOURNAL OF PROTEOME RESEARCH. 2016;15(10):3473-3480Hong M-G; Lee W; Nilsson P; Pawitan Y; Schwenk JM
- Article: CANCER EPIDEMIOLOGY. 2016;44:40-43Vasan SK; Hwang J; Rostgaard K; Nyren O; Ullum H; Pedersen OBV; Erikstrup C; Melbye M; Hjalgrim H; Pawitan Y; Edgren G
- Article: STATISTICS IN MEDICINE. 2016;35(18):3203-3212Lee D; Ganna A; Pawitan Y; Lee W
- Article: BIOINFORMATICS. 2016;32(14):2128-2135Trung NV; Wills QF; Kalari KR; Niu N; Wang L; Rantalainen M; Pawitan Y
- Article: GENETIC EPIDEMIOLOGY. 2016;40(5):416-424Lee W; Sjolander A; Pawitan Y
- Article: ALZHEIMERS & DEMENTIA. 2016;12(6):645-653Allen GI; Amoroso N; Anghel C; Balagurusamy V; Bare CJ; Beaton D; Bellotti R; Bennett DA; Boehme KL; Boutros PC; Caberlotto L; Caloian C; Campbell F; Chaibub Neto E; Chang Y-C; Chen B; Chen C-Y; Chien T-Y; Clark T; Das S; Davatzikos C; Deng J; Dillenberger D; Dobson RJB; Dong Q; Doshi J; Duma D; Errico R; Erus G; Everett E; Fardo DW; Friend SH; Froehlich H; Gan J; St George-Hyslop P; Ghosh SS; Glaab E; Green RC; Guan Y; Hong M-Y; Huang C; Hwang J; Ibrahim J; Inglese P; Iyappan A; Jiang Q; Katsumata Y; Kauwe JSK; Klein A; Kong D; Krause R; Lalonde E; Lauria M; Lee E; Lin X; Liu Z; Livingstone J; Logsdon BA; Lovestone S; Ma T-W; Malhotra A; Mangravite LM; Maxwell TJ; Merrill E; Nagorski J; Namasivayam A; Narayan M; Naz M; Newhouse SJ; Norman TC; Nurtdinov RN; Oyang Y-J; Pawitan Y; Peng S; Peters MA; Piccolo SR; Praveen P; Priami C; Sabelnykova VY; Senger P; Shen X; Simmons A; Sotiras A; Stolovitzky G; Tangaro S; Tateo A; Tung Y-A; Tustison NJ; Varol E; Vradenburg G; Weiner MW; Xiao G; Xie L; Xie Y; Xu J; Yang H; Zhan X; Zhou Y; Zhu F; Zhu H; Zhu S
- Article: EUROPEAN JOURNAL OF EPIDEMIOLOGY. 2016;31(6):575-582Dahlqwist E; Zetterqvist J; Pawitan Y; Sjolander A
- Article: TWIN RESEARCH AND HUMAN GENETICS. 2016;19(2):97-103Magnusson PKE; Lee D; Chen X; Szatkiewicz J; Pramana S; Teo S; Sullivan PF; Feuk L; Pawitan Y
- Article: BIOSTATISTICS. 2016;17(2):264-276Zetterqvist J; Vansteelandt S; Pawitan Y; Sjolander A
- Article: PLOS ONE. 2016;11(1):e0145545Peng Z; Andersson K; Lindholm J; Dethlefsen O; Pramana S; Pawitan Y; Nister M; Nilsson S; Li C
- Article: METABOLOMICS. 2016;12(1):4Ganna A; Fall T; Salihovic S; Lee W; Broeckling CD; Kumar J; Hagg S; Stenemo M; Magnusson PKE; Prenni JE; Lind L; Pawitan Y; Ingelsson E
- Article: HUMAN MOLECULAR GENETICS. 2015;24(23):6849-6860Hagg S; Ganna A; Van der Laan SW; Esko T; Pers TH; Locke AE; Berndt SI; Justice AE; Kahali B; Siemelink MA; Pasterkamp G; Strachan DP; Speliotes EK; North KE; Loos RJF; Hirschhorn JN; Pawitan Y; Ingelsson E
- Article: COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2015;89:147-157Lee S; Pawitan Y; Lee Y
- Article: BIOINFORMATICS. 2015;31(16):2607-2613Suo C; Hrydziuszko O; Lee D; Pramana S; Saputra D; Joshi H; Calza S; Pawitan Y
- Article: BRIEFINGS IN BIOINFORMATICS. 2015;16(4):563-575Ganna A; Lee D; Ingelsson E; Pawitan Y
- Article: ONCOTARGET. 2015;6(16):14139-14152Lazar V; Rubin E; Depil S; Pawitan Y; Martini J-F; Gomez-Navarro J; Yver A; Kan Z; Dry JR; Kehren J; Validire P; Rodon J; Vielh P; Ducreux M; Galbraith S; Lehnert M; Onn A; Berger R; Pierotti MA; Porgador A; Pramesh CS; Ye D-W; Carvalho AL; Batist G; Le Chevalier T; Morice P; Besse B; Vassal G; Mortlock A; Hansson J; Berindan-Neagoe I; Dann R; Haspel J; Irimie A; Laderman S; Nechushtan H; Al Omari AS; Haywood T; Bresson C; Soo KC; Osman I; Mata H; Lee JJ; Jhaveri K; Meurice G; Palmer G; Lacroix L; Koscielny S; Eterovic KA; Blay J-Y; Buller R; Eggermont A; Schilsky RL; Mendelsohn J; Soria J-C; Rothenberg M; Scoazec J-Y; Hong WK; Kurzrock R
- Article: CARCINOGENESIS. 2015;36(6):632-638Sinnott JA; Rider JR; Carlsson J; Gerke T; Tyekucheva S; Penney KL; Sesso HD; Loda M; Fall K; Stampfer MJ; Mucci LA; Pawitan Y; Andersson S-O; Andren O
- Journal article: JOURNAL OF CLINICAL ONCOLOGY. 2015;33(15_suppl):7524Mendelsohn J; Lazar V; Rubin E; Pawitan Y; Bresson C; Soria J-C; Eggermont A; Wunder F; Scoazec J-Y; Hong WK; Blay J-Y; Schilsky RL; Kurzrock R
- Article: EUROPEAN JOURNAL OF CANCER. 2015;51(6):751-757Pawitan Y; Yin L; Setiawan A; Auer G; Smedby KE; Czene K
- Article: CANCER RESEARCH. 2015;75(7):1187-1190Schwaederle M; Lazar V; Validire P; Hansson J; Lacroix L; Soria J-C; Pawitan Y; Kurzrock R
- Article: JOURNAL OF APPLIED STATISTICS. 2015;42(1):12-26Gusnanto A; Pawitan Y
- Article: STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY. 2015;14(5):481-495Lee W; Lee D; Pawitan Y
- Article: BIOMED RESEARCH INTERNATIONAL. 2015;2015:462549-13Lee W; Alexeyenko A; Pernemalm M; Guegan J; Dessen P; Lazar V; Lehtio J; Pawitan Y
- Article: EUROPEAN JOURNAL OF EPIDEMIOLOGY. 2014;29(11):813-820Sjolander A; Lee W; Kallberg H; Pawitan Y
- Article: PLOS ONE. 2014;9(10):e109610Peng Z; Andersson K; Lindholm J; Bodin I; Pramana S; Pawitan Y; Nister M; Nilsson S; Li C
- Article: BIOMETRICS. 2014;70(3):500-505Sjolander A; Lee W; Kallberg H; Pawitan Y
- Article: NATURE GENETICS. 2014;46(8):881-885Gaugler T; Klei L; Sanders SJ; Bodea CA; Goldberg AP; Lee AB; Mahajan M; Manaa D; Pawitan Y; Reichert J; Ripke S; Sandin S; Sklar P; Svantesson O; Reichenberg A; Hultman CM; Devlin B; Roeder K; Buxbaum JD
- Article: BMC CANCER. 2014;14:391Holmes MD; Olsson H; Pawitan Y; Holm J; Lundholm C; Andersson TM-L; Adami H-O; Askling J; Smedby KE
- Article: AMERICAN STATISTICIAN. 2014;68(2):93-97Lee W; Pawitan Y
- Article: PLOS PATHOGENS. 2014;10(4):e1004038Bachmann J; Burte F; Pramana S; Conte I; Brown BJ; Orimadegun AE; Ajetunmobi WA; Afolabi NK; Akinkunmi F; Omokhodion S; Akinbami FO; Shokunbi WA; Kampf C; Pawitan Y; Uhlen M; Sodeinde O; Schwenk JM; Wahlgren M; Fernandez-Reyes D; Nilsson P
- Article: PROSTATE CANCER AND PROSTATIC DISEASES. 2014;17(1):81-90Peng Z; Skoog L; Hellborg H; Jonstam G; Wingmo I-L; Hjalm-Eriksson M; Harmenberg U; Cedermark GC; Andersson K; Ahrlund-Richter L; Pramana S; Pawitan Y; Nister M; Nilsson S; Li C
- Article: BIOINFORMATICS. 2014;30(4):506-513Suo C; Calza S; Salim A; Pawitan Y
- Article: STATISTICS IN MEDICINE. 2013;32(30):5340-5352Lee D; Lee Y; Pawitan Y; Lee W
- Article: BMC MEDICAL GENOMICS. 2013;6:53Lazar V; Suo C; Orear C; van den Oord J; Balogh Z; Guegan J; Job B; Meurice G; Ripoche H; Calza S; Hasmats J; Lundeberg J; Lacroix L; Vielh P; Dufour F; Lehtio J; Napieralski R; Eggermont A; Schmitt M; Cadranel J; Besse B; Girard P; Blackhall F; Validire P; Soria J-C; Dessen P; Hansson J; Pawitan Y
- Article: BRITISH JOURNAL OF CANCER. 2013;109(7):1921-1925Jonsson F; Yin L; Lundholm C; Smedby KE; Czene K; Pawitan Y
- Article: JOURNAL OF PROTEOME RESEARCH. 2013;12(9):3934-3943Pernemalm M; De Petris L; Branca RM; Forshed J; Kanter L; Soria J-C; Girard P; Validire P; Pawitan Y; van den Oord J; Lazar V; Pahlman S; Lewensohn R; Lehtio J
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- Article: PLOS ONE. 2012;7(7):e41783Frisell T; Pawitan Y; Langstrom N
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- Article: AMERICAN JOURNAL OF TRANSPLANTATION. 2011;11(11):2472-2482Fernberg P; Edgren G; Adami J; Ingvar A; Bellocco R; Tufveson G; Hoglund P; Kinch A; Simard JF; Baecklund E; Lindelof B; Pawitan Y; Smedby KE
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- Article: JOURNAL OF HUMAN GENETICS. 2011;56(7):524-533Teo S-M; Ku C-S; Naidoo N; Hall P; Chia K-S; Salim A; Pawitan Y
- Article: JOURNAL OF CLINICAL ONCOLOGY. 2011;29(17):2391-2396Penney KL; Sinnott JA; Fall K; Pawitan Y; Hoshida Y; Kraft P; Stark JR; Fiorentino M; Perner S; Finn S; Calza S; Flavin R; Freedman ML; Setlur S; Sesso HD; Andersson S-O; Martin N; Kantoff PW; Johansson J-E; Adami H-O; Rubin MA; Loda M; Golub TR; Andren O; Stampfer MJ; Mucci LA
- Article: BIOINFORMATICS. 2011;27(11):1555-1561Teo SM; Pawitan Y; Kumar V; Thalamuthu A; Seielstad M; Chia KS; Salim A
- Article: STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY. 2011;10(1):1-24Lee W; Lee D; Lee Y; Pawitan Y
- Article: STATISTICS IN MEDICINE. 2010;29(30):3258-3266Yip BH; Moger TA; Pawitan Y
- Article: RNA. 2010;16(12):2293-2303Suo C; Salim A; Chia K-S; Pawitan Y; Calza S
- Article: HUMAN MUTATION. 2010;31(7):851-857Ku C-S; Pawitan Y; Sim X; Ong RTH; Seielstad M; Lee EJD; Teo Y-Y; Chia K-S; Salim A
- Article: BMC BIOINFORMATICS. 2010;11:296Lee D; Lee W; Lee Y; Pawitan Y
- Article: BEHAVIOR GENETICS. 2010;40(3):404-414Yip BH; Reilly M; Cnattingius S; Pawitan Y
- Article: BMC BIOINFORMATICS. 2010;11:147Mei TS; Salim A; Calza S; Seng KC; Seng CK; Pawitan Y
- Article: BMC MEDICAL GENOMICS. 2010;3:8Sboner A; Demichelis F; Calza S; Pawitan Y; Setlur SR; Hoshida Y; Perner S; Adami H-O; Fall K; Mucci LA; Kantoff PW; Stampfer M; Andersson S-O; Varenhorst E; Johansson J-E; Gerstein MB; Golub TR; Rubin MA; Andren O
- Article: METHODS IN MOLECULAR BIOLOGY. 2010;673:37-52Calza S; Pawitan Y
- Article: STATISTICS IN MEDICINE. 2009;28(30):3798-3810Huang J; Salim A; Lei K; O'Sullivan K; Pawitan Y
- Article: PLOS ONE. 2009;4(12):e7969Pawitan Y; Seng KC; Magnusson PKE
- Article: AMERICAN JOURNAL OF EPIDEMIOLOGY. 2009;170(11):1365-1372Svensson AC; Sandin S; Cnattingius S; Reilly M; Pawitan Y; Hultman CM; Lichtenstein P
- Article: BMC BIOINFORMATICS. 2009;10:272Tan CS; Salim A; Ploner A; Lehtio J; Chia KS; Pawitan Y
- Article: HUMAN GENETICS. 2009;126(2):289-301Hong M-G; Pawitan Y; Magnusson PKE; Prince JA
- Article: LANCET. 2009;373(9659):234-239Lichtenstein P; Yip BH; Bjork C; Pawitan Y; Cannon TD; Sullivan PF; Hultman CM
- Article: BMC CANCER. 2008;8:368Chia SE; Tan CS; Lim GH; Sim X; Pawitan Y; Reilly M; Ali SM; Lau W; Chia KS
- Article: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA. 2008;105(47):18490-18495Weichselbaum RR; Ishwaran H; Yoon T; Nuyten DSA; Baker SW; Khodarev N; Su AW; Shaikh AY; Roach P; Kreike B; Roizman B; Bergh J; Pawitan Y; de Vijver MJV; Minn AJ
- Article: EPIDEMIOLOGY. 2008;19(5):659-665Johansson S; Iliadou A; Bergvall N; de Faire U; Kramer MS; Pawitan Y; Pedersen NL; Norman M; Lichtenstein P; Cnattingius S
- Article: CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION. 2008;17(7):1682-1688Mucci LA; Pawitan Y; Demichelis F; Fall K; Stark JR; Adami H-O; Andersson S-O; Andren O; Eisenstein A; Holmberg L; Huang W; Kantoff PW; Kim R; Perner S; Stampfer MJ; Johansson J-E; Rubin MA
- Article: JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE. 2008;100(11):815-825Setlur SR; Mertz KD; Hoshida Y; Demichelis F; Lupien M; Perner S; Sboner A; Pawitan Y; Andren O; Johnson LA; Tang J; Adami H-O; Calza S; Chinnaiyan AM; Rhodes D; Tomlins S; Fall K; Mucci LA; Kantoff PW; Stampfer MJ; Andersson S-O; Varenhorst E; Johansson J-E; Brown M; Golub TR; Rubin MA
- Article: JOURNAL OF PROTEOME RESEARCH. 2008;7(6):2332-2341Forshed J; Pernemalm M; Tan CS; Lindberg M; Kanter L; Pawitan Y; Lewensohn R; Stenke L; Lehtio J
- Article: BIOINFORMATICS. 2008;24(9):1168-1174Demissie M; Mascialino B; Calza S; Pawitan Y
- Article: CANCER BIOLOGY & THERAPY. 2008;7(5):699-708Berglind H; Pawitan Y; Kato S; Ishioka C; Soussi T
- Article: STATISTICS IN MEDICINE. 2008;27(7):1062-1074Moger TA; Pawitan Y; Borgan O
- Article: STATISTICS IN MEDICINE. 2008;27(7):1086-1105Yip BH; Bjork C; Lichtenstein P; Hultman CM; Pawitan Y
- Article: BMC BIOINFORMATICS. 2008;9:140Calza S; Valentini D; Pawitan Y
- Article: INTERNATIONAL JOURNAL OF EPIDEMIOLOGY. 2008;37(1):185-192Bergvall N; Lindam A; Pawitan Y; Lichtenstein P; Cnattingius S; Iliadou A
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- Article: BIOINFORMATICS. 2007;23(18):2463-2469Huang J; Gusnanto A; O'Sullivan K; Staaf J; Borg A; Pawitan Y
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- Article: NUCLEIC ACIDS RESEARCH. 2007;35(16):e102Calza S; Raffelsberger W; Ploner A; Sahel J; Leveillard T; Pawitan Y
- Article: GENES CHROMOSOMES & CANCER. 2007;46(1):87-97Gene expression in 16q is associated with survival and differs between Sorlie breast cancer subtypesWennmalm K; Calza S; Ploner A; Hall P; Bjoehle J; Klaar S; Smeds J; Pawitan Y; Bergh J
- Article: BIOINFORMATICS. 2006;22(24):3025-3031Pawitan Y; Calza S; Ploner A
- Article: PROTEOMICS. 2006;6(23):6124-6133Tan CS; Ploner A; Quandt A; Lehtio J; Pernemalm M; Lewensohn R; Pawitan Y
- Article: INTERNATIONAL JOURNAL OF EPIDEMIOLOGY. 2006;35(6):1495-1503Yip BH; Pawitan Y; Czene K
- Article: CANCER RESEARCH. 2006;66(21):10292-10301Ivshina AV; George J; Senko O; Mow B; Putti TC; Smeds J; Lindahl T; Pawitan Y; Hall P; Nordgren H; Wong JEL; Liu ET; Bergh J; Kuznetsov VA; Miller LD
- Article: STATISTICS IN MEDICINE. 2006;25(18):3110-3123Lindstrom L; Pawitan Y; Reilly M; Hemminki K; Lichtenstein P; Czene K
- Article: CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION. 2006;15(9):1630-1635Kronenwett U; Ploner A; Zetterberg A; Bergh J; Hall P; Auer G; Pawitan Y
- Article: BMC MEDICINE. 2006;4:16Hall P; Ploner A; Bjohle J; Huang F; Lin C-Y; Liu ET; Miller LD; Nordgren H; Pawitan Y; Shaw P; Skoog L; Smeds J; Wedren S; Ohd J; Bergh J
- Article: BIOINFORMATICS. 2006;22(12):1515-1523Tan CS; Ploner A; Quandt A; Lehtio J; Pawitan Y
- Article: INTERNATIONAL JOURNAL OF CANCER. 2006;118(9):2298-2302Fernberg P; Odenbro A; Bellocco R; Boffetta P; Pawitan Y; Adami J
- Article: BIOINFORMATICS. 2006;22(5):556-565Ploner A; Calza S; Gusnanto A; Pawitan Y
- Article: AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY. 2006;194(2):475-479Svensson AC; Pawitan Y; Cnattingius S; Reilly M; Lichtenstein P
- Article: BREAST CANCER RESEARCH. 2006;8(4):R34Calza S; Hall P; Auer G; Bjohle J; Klaar S; Kronenwett U; T Liu E; Miller L; Ploner A; Smeds J; Bergh J; Pawitan Y
- Article: GENETIC EPIDEMIOLOGY. 2006;30(1):37-47Noh M; Yip B; Lee Y; Pawitan Y
- Article: BIOINFORMATICS. 2005;21(20):3865-3872Pawitan Y; Murthy KRK; Michiels S; Ploner A
- Article: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA. 2005;102(38):13550-13555Miller LD; Smeds J; George J; Vega VB; Vergara L; Ploner A; Pawitan Y; Hall P; Klaar S; Liu ET; Bergh J
- Article: GENETIC EPIDEMIOLOGY. 2005;29(1):68-75Noh M; Lee Y; Pawitan Y
- Article: BIOINFORMATICS. 2005;21(13):3017-3024Pawitan Y; Michiels S; Koscielny S; Gusnanto A; Ploner A
- Article: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS. 2005;54:555-573Salim A; Pawitan Y; Bond K
- Article: EUROPEAN JOURNAL OF HAEMATOLOGY. 2005;74(6):466-480Kuchinskaya E; Heyman M; Grandér D; Linderholm M; Söderhäll S; Zaritskey A; Nordgren A; Porwit-MacDonald A; Zueva E; Pawitan Y; Corcoran M; Nordenskjöld M; Blennow E
- Article: BMC BIOINFORMATICS. 2005;6:80Ploner A; Miller LD; Hall P; Bergh J; Pawitan Y
- Article: STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY. 2005;4:Article26Gusnanto A; Ploner A; Pawitan Y
- Article: INTERNATIONAL JOURNAL OF CANCER. 2005;113(2):302-306Chia KS; Reiliy M; Tan CS; Lee J; Pawitan Y; Adami HO; Ha P; Mow B
- Article: IEEE TRANSACTIONS ON MEDICAL IMAGING. 2005;24(1):122-129Pawitan Y; Bettinardi V; Teräs M
- Article: ANNALS OF NEUROLOGY. 2005;57(1):27-33Wirdefeldt K; Gatz M; Pawitan Y; Pedersen NL
- Article: BREAST CANCER RESEARCH. 2005;7(6):R953-R964Pawitan Y; Bjöhle J; Amler L; Borg AL; Egyhazi S; Hall P; Han X; Holmberg L; Huang F; Klaar S; Liu ET; Miller L; Nordgren H; Ploner A; Sandelin K; Shaw PM; Smeds J; Skoog L; Wedrén S; Bergh J
- Article: AMERICAN JOURNAL OF MEDICAL GENETICS PART A. 2004;130A(4):365-371Cnattingius S; Reilly M; Pawitan Y; Lichtenstein P
- Article: STATISTICS IN MEDICINE. 2004;23(19):3013-3032Reilly M; Salim A; Lawlor E; Smith O; Temperley I; Pawitan Y
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- Article: PREVENTIVE VETERINARY MEDICINE. 2004;62(4):267-283Pawitan Y; Griffin JM; Collins JD
- Article: STATISTICS IN MEDICINE. 2004;23(3):449-465Pawitan Y; Reilly M; Nilsson E; Cnattingius S; Lichtenstein P
- Article: CANCER RESEARCH. 2004;64(3):904-909Kronenwett U; Huwendiek S; Östring C; Portwood N; Roblick UJ; Pawitan Y; Alaiya A; Sennerstam R; Zetterberg A; Auer G
- Article: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION. 2003;73(12):853-865Pawitan Y; Huang J
- Article: STATISTICAL MODELLING. 2003;3(2):79-98Salim A; Pawitan Y
- Article: JOURNAL OF CHEMOMETRICS. 2003;17(3):174-185Gusnanto A; Pawitan Y; Huang J; Lane B
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- Preprint: BIORXIV. 2018Hong M-G; Dodig-Crnković T; Chen X; Drobin K; Lee W; Wang Y; Edfors F; Kotol D; Thomas CE; Sjöberg R; Odeberg J; Hamsten A; Silveira A; Hall P; Nilsson P; Pawitan Y; Hägg S; Uhlén M; Pedersen N; Magnusson P; Schwenk J
- Book: 2018Lee Y; Nelder JA; Pawitan Y
- Review: CANCER. 2017;123(9):1490-1496Pettersson A; Gerke T; Fall K; Pawitan Y; Holmberg L; Giovannucci EL; Kantoff PW; Adami H-O; Rider JR; Mucci LA
- Preprint: ARXIV. 2015Shen X; Ning Z; Pawitan Y
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- Review: MOLECULAR PSYCHIATRY. 2013;18(2):141-153Ku CS; Polychronakos C; Tan EK; Naidoo N; Pawitan Y; Roukos DH; Mort M; Cooper DN
- Review: BIOINFORMATICS. 2012;28(21):2711-2718Teo SM; Pawitan Y; Ku CS; Chia KS; Salim A
- Published conference paper: STATISTICS IN MEDICINE. 2012;31(11-12):1177-1189Lee W; Gusnanto A; Salim A; Magnusson P; Sim X; Tai ES; Pawitan Y
- Review: EXPERT REVIEW OF MOLECULAR DIAGNOSTICS. 2012;12(3):241-251Ku C-S; Wu M; Cooper DN; Naidoo N; Pawitan Y; Pang B; Lacopetta B; Soong R
- Review: EXPERT REVIEW OF MOLECULAR DIAGNOSTICS. 2012;12(2):159-173Ku C-S; Wu M; Cooper DN; Naidoo N; Pawitan Y; Pang B; Iacopetta B; Soong R
- Review: HUMAN GENETICS. 2011;129(4):351-370Ku C-S; Naidoo N; Pawitan Y
- Review: HUMAN GENETICS. 2011;129(1):1-15Ku CS; Naidoo N; Teo SM; Pawitan Y
- Review: JOURNAL OF HUMAN GENETICS. 2010;55(7):403-415The discovery of human genetic variations and their use as disease markers: past, present and futureKu CS; Loy EY; Salim A; Pawitan Y; Chia KS
- Review: JOURNAL OF HUMAN GENETICS. 2010;55(4):195-206Ku CS; Loy EY; Pawitan Y; Chia KS
- Editorial comment: AMERICAN JOURNAL OF EPIDEMIOLOGY. 2009;170(11):1386-1387Svensson AC; Sandin S; Cnattingius S; Reilly M; Pawitan Y; Hultman CM; Lichtenstein P
- Review: CURRENT OPINION IN LIPIDOLOGY. 2007;18(2):187-193Gusnanto A; Calza S; Pawitan Y
- Meeting abstract: SCHIZOPHRENIA RESEARCH. 2006;81:3Lichtenstein P; Yip B; Björk C; Pawitan Y; Hultman C
- Letter: STATISTICS IN MEDICINE. 2005;24(10):1617-1618Pawitan Y; Reilly M; Nilsson E; Cnattingius S; Lichtenstein P
- Published conference paper: LECTURE NOTES IN COMPUTER SCIENCE. 2005;3695:140-150Quandt A; Ploner A; Tan CS; Lehtiö J; Pawitan Y
- Published conference paper: ANNALS OF ONCOLOGY. 2005;16:ii195-ii202Smeds J; Miller LD; Bjöhle J; Hall P; Klaar S; Liu ET; Pawitan Y; Ploner A; Bergh J
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Grants
- Swedish Research Council1 January 2023 - 31 December 2025Fragile X syndrome (FXS) and Creatine Transporter Deficiency (CTD) are the two most common causes of X-linked intellectual disability. FXS and CTD share common clinical traits, such as cognitive dysfunction, autistic-like features, motor abnormalities and seizures. They also have similar pathophysiology, including alterations of brain energetics. There is no cure for these disorders and the efficacy study of potential treatments is hindered by the scarcity of unbiased, quantitative, non-invasive biomarkers for monitoring brain function. This is an important problem, because behavioural endpoints is subjective, and the use of objective measures is crucial to assess efficacy of new drugs. Since abnormal hemodynamic responses (HR) to sensory stimulation have been reported in preclinical studies of FXS and CTD, the objective of this project is to exploit optical imaging techniques to devise a non-invasive biomarker for these disorders. We will use imaging of intrinsic optical signals (IOS) in animal models and functional near-infrared spectroscopy (fNIRS) in patients. These non-invasive tools allow sensitive detection the changes of hemoglobin species and local blood flow inside the brain, thus providing an indirect measure of neuronal activity. We will: 1) test IOS responses between mutants and controls in animal models of FXS and CTD2) investigate molecular mechanisms underlying altered IOS3) validate the clinical relevance using fNIRS in patient population.
- Swedish Research Council1 January 2023 - 31 December 2025Heritability and genetic correlation are central parameters for understanding the genetic architecture of complex diseases. It is essential to assess the enrichment of these parameters in genomic functional regions. Making use of genome-wide association study summary statistics resources, linkage disequilibrium (LD) score regression was developed for the estimation of heritability and genetic correlation, without accessing individual-level data. Stratified LD score regression (S-LDSC) can assess heritability enrichment on various genome annotations. However, LD score regression does not consider the full linkage information in the genome, and certain types of genomic annotations, including pairwise topological interactions between DNA segments, can hardly be considered in S-LDSC. In 2020, the PI published the high-definition likelihood (HDL) method in Nature Genetics, improving the estimation precision of LD score regression, however, the stratified likelihood model is yet to be developed. Following the demand of the research community, this project aims to develop the stratified high-definition likelihood (S-HDL) method, including both the statistical genetics model and an efficient computational algorithm. The method will be evaluated by both simulations and real data applications. The new method will identify significantly more functional enrichment results for human complex diseases, so that will better reveal the underlying genetic architecture and disease etiology.
- Detection of biomarkers by analysis of "Next generation" sequencing data.Swedish Cancer Society1 January 2018Molecular research is currently dominated by sequence-based technology, partly because the cost has decreased dramatically but also because the technology promises very detailed information on individual cancers. But many challenges remainAlthough we can produce a correct list of mutations in a single cancer, it is far from self-evident what they mean in terms of cancer biology or what one can clinically use it for. There is still a large gap between the list of mutations and clinical decisions for which treatment to use for the individual. The overall goals of our research include: (i) computer modeling and analysis of the large-scale molecular data currently dominated by DNA and RNA sequence data, and (ii) integration of multiple omics data to improve disease prognosis. As cancer cells develop, many genomic changes such as mutations or copy variation accumulate in the cell. An important step towards better biological understanding and treatment is to try to separate the genomic cause / effect changes from independent / accompanying ones. It is the effect changes that the cancer cells depend on for survival and growth. Our hope is to develop robust methods for identifying cancer cells by integrating omics data, not just the obvious genomics and transcriptomics data such as mutations, copying variability and RNA expression, but also by using biology databases and data networks for interaction genomics such as gene or protein interaction. With the same approach, we have previously shown improved prognoses for breast cancer survival, and we plan to continue the research and development by using the technique of omission data on other cancers.
- Detection of biomarkers by analysis of "Next generation" sequencing data.Swedish Cancer Society1 January 2017Molecular research is currently dominated by sequence-based technology, partly because the cost has decreased dramatically but also because the technology promises very detailed information on individual cancers. But many challenges remainAlthough we can produce a correct list of mutations in a single cancer, it is far from self-evident what they mean in terms of cancer biology or what one can clinically use it for. There is still a large gap between the list of mutations and clinical decisions for which treatment to use for the individual. The overall goals of our research include: (i) computer modeling and analysis of the large-scale molecular data currently dominated by DNA and RNA sequence data, and (ii) integration of multiple omics data to improve disease prognosis. As cancer cells develop, many genomic changes such as mutations or copy variation accumulate in the cell. An important step towards better biological understanding and treatment is to try to separate the genomic cause / effect changes from independent / accompanying ones. It is the effect changes that the cancer cells depend on for survival and growth. Our hope is to develop robust methods for identifying cancer cells by integrating omics data, not just the obvious genomics and transcriptomics data such as mutations, copying variability and RNA expression, but also by using biology databases and data networks for interaction genomics such as gene or protein interaction. With the same approach, we have previously shown improved prognoses for breast cancer survival, and we plan to continue the research and development by using the technique of omission data on other cancers.
- Swedish Research Council1 January 2017 - 31 December 2020
- Detection of biomarkers by analysis of "Next generation" sequencing data.Swedish Cancer Society1 January 2016Molecular research is currently dominated by sequence-based technology, partly because the cost has decreased dramatically but also because the technology promises very detailed information on individual cancers. But many challenges remainAlthough we can produce a correct list of mutations in a single cancer, it is far from self-evident what they mean in terms of cancer biology or what one can clinically use it for. There is still a large gap between the list of mutations and clinical decisions for which treatment to use for the individual. The overall goals of our research include: (i) computer modeling and analysis of the large-scale molecular data currently dominated by DNA and RNA sequence data, and (ii) integration of multiple omics data to improve disease prognosis. As cancer cells develop, many genomic changes such as mutations or copy variation accumulate in the cell. An important step towards better biological understanding and treatment is to try to separate the genomic cause / effect changes from independent / accompanying ones. It is the effect changes that the cancer cells depend on for survival and growth. Our hope is to develop robust methods for identifying cancer cells by integrating omics data, not just the obvious genomics and transcriptomics data such as mutations, copying variability and RNA expression, but also by using biology databases and data networks for interaction genomics such as gene or protein interaction. With the same approach, we have previously shown improved prognoses for breast cancer survival, and we plan to continue the research and development by using the technique of omission data on other cancers.
- Use next-generation sequence data to find biomarkers for cancerSwedish Cancer Society1 January 2015The growth of large-scale data sets continues unabated with the advent of next generation sequencing. Sequencing can reveal unsolicited information on a single tumor's mutation spectrum. An application of sequencing can be used to detect person-specific cancer biomarkers for treatment and follow-up decisions. This means that we have now reached the highly anticipated area of personal medication. Although the cost of sequencing is now considered affordable, around US $ 5,000 for the entire genome, it presents data that generates great challenges, both in basic IT infrastructure and statistical analysis. The primary objective of our research group is to develop statistical and bioinformatic tools and methods for analyzing large-scale data sets within molecular medicine. Currently, we focus on the challenges we face when analyzing the next generation of sequencing data. We pay special attention to searching for biomarkers for cancer. The specific problems we address are: (i) detection of mutations from sequence data, (ii) identification of so-called control genes and biological processes by means of integration of several different types of molecular data, (iii) identification of group-specific markers for breast cancer. We hope to answer the above problems by analyzing the next generation of sequencing data on about 400 breast cancer patients. The data set has already been collected via Cancer Genome Atlas, a large NIH-funded study in cancer genome where approximately 5,000 cancer samples of 20 different cancers have been sequenced. As this is one of the largest collections of ordered data for breast cancer, we hope, with our analyzes, to be able to identify new mutations of breast cancer, and among these mutations, determine which are the most likely mutations that drive the development of the individual cancer.
- Use next-generation sequence data to find biomarkers for cancerSwedish Cancer Society1 January 2014The growth of large-scale data sets continues unabated with the advent of next generation sequencing. Sequencing can reveal unsolicited information on a single tumor's mutation spectrum. An application of sequencing can be used to detect person-specific cancer biomarkers for treatment and follow-up decisions. This means that we have now reached the highly anticipated area of personal medication. Although the cost of sequencing is now considered affordable, around US $ 5,000 for the entire genome, it presents data that generates great challenges, both in basic IT infrastructure and statistical analysis. The primary objective of our research group is to develop statistical and bioinformatic tools and methods for analyzing large-scale data sets within molecular medicine. Currently, we focus on the challenges we face when analyzing the next generation of sequencing data. We pay special attention to searching for biomarkers for cancer. The specific problems we address are: (i) detection of mutations from sequence data, (ii) identification of so-called control genes and biological processes by means of integration of several different types of molecular data, (iii) identification of group-specific markers for breast cancer. We hope to answer the above problems by analyzing the next generation of sequencing data on about 400 breast cancer patients. The data set has already been collected via Cancer Genome Atlas, a large NIH-funded study in cancer genome where approximately 5,000 cancer samples of 20 different cancers have been sequenced. As this is one of the largest collections of ordered data for breast cancer, we hope, with our analyzes, to be able to identify new mutations of breast cancer, and among these mutations, determine which are the most likely mutations that drive the development of the individual cancer.
- Swedish Research Council1 January 2014 - 31 December 2016
- Swedish Research Council1 January 2012 - 31 December 2015
- Swedish Research Council1 January 2010 - 31 December 2012
Employments
- Professor, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 2002-