Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Scott Kulm"'
Autor:
Yajas Shah, Scott Kulm, Jones T Nauseef, Zhengming Chen, Olivier Elemento, Kevin H Kensler, Ravi N Sharaf
Publikováno v:
PLoS Computational Biology, Vol 20, Iss 4, p e1011990 (2024)
Prostate cancer is a heritable disease with ancestry-biased incidence and mortality. Polygenic risk scores (PRSs) offer promising advancements in predicting disease risk, including prostate cancer. While their accuracy continues to improve, research
Externí odkaz:
https://doaj.org/article/9b1c0fad8d784c70bdca6d450b9673f8
Autor:
George B. Busby, Scott Kulm, Alessandro Bolli, Jen Kintzle, Paolo Di Domenico, Giordano Bottà
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)
Abstract Clinical implementation of new prediction models requires evaluation of their utility in a broad range of intended use populations. Here we develop and validate ancestry-specific Polygenic Risk Scores (PRSs) for Coronary Artery Disease (CAD)
Externí odkaz:
https://doaj.org/article/44e7791f217540b3aa1a466ee00c865a
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Abstract Both clinical and genetic factors drive the risk of venous thromboembolism. However, whether clinically recorded risk factors and genetic variants can be combined into a clinically applicable predictive score remains unknown. Using Cox propo
Externí odkaz:
https://doaj.org/article/6be609cfb3614d65b0a91ab01c4fbf09
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-4 (2021)
Externí odkaz:
https://doaj.org/article/6e923570e8be4f9aa9377e2baf6afd98
Autor:
Alessandro Pastore, Federico Gaiti, Sydney X. Lu, Ryan M. Brand, Scott Kulm, Ronan Chaligne, Hongcang Gu, Kevin Y. Huang, Elena K. Stamenova, Wendy Béguelin, Yanwen Jiang, Rafael C. Schulman, Kyu-Tae Kim, Alicia Alonso, John N. Allan, Richard R. Furman, Andreas Gnirke, Catherine J. Wu, Ari M. Melnick, Alexander Meissner, Bradley E. Bernstein, Omar Abdel-Wahab, Dan A. Landau
Publikováno v:
Nature Communications, Vol 10, Iss 1, Pp 1-11 (2019)
In chronic lymphocytic leukemia (CLL), evolution is driven by transcriptional and epigenetic heterogeneity. Here, the authors integrate epigenomic analyses to show how intra-tumoral epigenetic diversity results in divergent chromatin states in CLL ce
Externí odkaz:
https://doaj.org/article/84f8fc2c23c040aca441459292bfd167
Publikováno v:
PLoS ONE, Vol 15, Iss 11, p e0241264 (2020)
BackgroundCoronavirus disease 2019 (Covid-19) has rapidly infected millions of people worldwide. Recent studies suggest that racial minorities and patients with comorbidities are at higher risk of Covid-19. In this study, we analyzed the effects of c
Externí odkaz:
https://doaj.org/article/bf0e112a8a9244d1932ce26f6971fe0e
Autor:
Scott Kulm, Austin C. Kaidi, David Kolin, Mark T. Langhans, Mathias P. Bostrom, Olivier Elemento, Tony S. Shen
Publikováno v:
The Journal of Arthroplasty.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49502de48d8d7016aec7abe7ca1a7724
https://doi.org/10.1016/j.arth.2023.05.006
https://doi.org/10.1016/j.arth.2023.05.006
Clinical implementation of new prediction models requires evaluation of their validity and utility in a broad range of intended use populations. Here we outline the development and validation of multiple ancestry-specific Polygenic Risk Scores (PRSs)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26f50b2a1971154ed0327e1f35f9373e
https://doi.org/10.21203/rs.3.rs-2840714/v1
https://doi.org/10.21203/rs.3.rs-2840714/v1
Autor:
Patawut Bovonratwet, Scott Kulm, David A. Kolin, Junho Song, Kyle W. Morse, Matthew E. Cunningham, Todd J. Albert, Harvinder S. Sandhu, Han Jo Kim, Sravisht Iyer, Olivier Elemento, Sheeraz A. Qureshi
Publikováno v:
Journal of Bone and Joint Surgery.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6359ec3819556c596865fc81bdce7d0d
https://doi.org/10.2106/jbjs.22.00872
https://doi.org/10.2106/jbjs.22.00872
Publikováno v:
JCO clinical cancer informatics. 6
PURPOSE The ability to accurately predict an individual's risk for cancer is critical to the implementation of precision prevention measures. Current cancer risk predictions are frequently made with simple models that use a few proven risk factors, s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5954c527ff5409058b8c768f9dda6764
https://pubmed.ncbi.nlm.nih.gov/35239414
https://pubmed.ncbi.nlm.nih.gov/35239414