Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Aaron Kershenbaum"'
Autor:
Marijana Vujkovic, Aaron Kershenbaum, Lisa Wray, Thomas McWilliams, Shannon Cannon, Meenakshi Devidas, Linda Stork, Richard Aplenc
Publikováno v:
Leukemia Research Reports, Vol 4, Iss 2, Pp 47-50 (2015)
Genetic variation in drug detoxification pathways may influence outcomes in pediatric acute lymphoblastic leukemia (ALL). We evaluated relapse risk and 24 variants in 17 genes in 714 patients in CCG-1961. Three TPMT and 1 MTR variant were associated
Externí odkaz:
https://doaj.org/article/5d39e4a3639244149da78a08e86267c5
Publikováno v:
PLoS ONE, Vol 4, Iss 3, p e4862 (2009)
Commonly-occurring disease etiology may involve complex combinations of genes and exposures resulting in etiologic heterogeneity. We present a computational algorithm that employs clique-finding for heterogeneity and multidimensionality in biomedical
Externí odkaz:
https://doaj.org/article/27405e9f13db4c1693e9ae51291e2fcc
Publikováno v:
2022 IEEE Integrated STEM Education Conference (ISEC).
Autor:
Lisa Wray, Marijana Vujkovic, Meenakshi Devidas, Linda C. Stork, Richard Aplenc, Shannon Cannon, Thomas McWilliams, Aaron Kershenbaum
Publikováno v:
Leukemia Research Reports
Leukemia Research Reports, Vol 4, Iss 2, Pp 47-50 (2015)
Leukemia Research Reports, Vol 4, Iss 2, Pp 47-50 (2015)
Genetic variation in drug detoxification pathways may influence outcomes in pediatric acute lymphoblastic leukemia (ALL). We evaluated relapse risk and 24 variants in 17 genes in 714 patients in CCG-1961. Three TPMT and 1 MTR variant were associated
Autor:
Robert Schiaffino, Jason H. Moore, Alicia Cutillo, Aaron Kershenbaum, Keitha Murray, Christian Darabos
Publikováno v:
Applications of Evolutionary Computation ISBN: 9783319312033
EvoApplications (1)
EvoApplications (1)
Networks representing complex biological interactions are often very intricate and rely on algorithmic tools for thorough quantitative analysis. In bi-layered graphs, identifying subgraphs of potential biological meaning relies on identifying bicliqu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f7d375edaae83f6d371aa028571f687
https://doi.org/10.1007/978-3-319-31204-0_10
https://doi.org/10.1007/978-3-319-31204-0_10
Autor:
Thomas McWilliams, Dana M. Sepe, Jinbo Chen, Timothy R. Rebbeck, Huaqing Zhao, Richard Aplenc, Mei La, Aaron Kershenbaum, Meenakshi Devidas, Beverly J. Lange
Publikováno v:
Pediatric Blood & Cancer. 58:695-700
Background—Recent studies suggest that polymorphisms in genes encoding enzymes involved in drug detoxification and metabolism may influence disease outcome in pediatric acute lymphoblastic leukemia (ALL). We sought to extend current knowledge by us
Publikováno v:
IBM Systems Journal. 46:135-149
In this paper we describe a graph-theoretical approach for pattern discovery that is especially useful in epidemiological research when applied to case-control studies involving categorical features such as genotypes and exposures. Whereas existing a
Autor:
Deqingyuzhen, Phillip Hirsch, Aaron Kershenbaum, Pui Lam Raymond Yu, Teresa Piliouras, Julie Mann, Jasmin Warner, Jeanne Lauer
Publikováno v:
2015 IEEE Integrated STEM Education Conference.
This paper discusses the importance of academic culture and its impacts on students and their motivation. Cultural challenges and obstacles to educational reform are explored. The expanding role of technology in educational instruction and driving cu
Autor:
Anthony Hasseldine, Prahlad T. Ram, Avi Ma'ayan, J. Jeremy Rice, Robert D. Blitzer, Narat J. Eungdamrong, Elizabeth A. Grace, Benjamin J. Dubin-Thaler, Susana R. Neves, Ravi Iyengar, Gustavo Stolovitzky, Aaron Kershenbaum, Sherry L. Jenkins, Gehzi Weng
Publikováno v:
Science. 309:1078-1083
We developed a model of 545 components (nodes) and 1259 interactions representing signaling pathways and cellular machines in the hippocampal CA1 neuron. Using graph theory methods, we analyzed ligand-induced signal flow through the system. Specifica
Autor:
Robert D. Johnson, Lawrence Koved, Harini Srinivasan, Darrell C. Reimer, Bowen Alpern, Aaron Kershenbaum, Edith Schonberg, Kavitha Srinivas
Publikováno v:
ISSTA
In this paper, we present an approach to automatically detect high impact coding errors in large Java applications which use frameworks. These high impact errors cause serious performance degradation and outages in real world production environments,