User profiles for "author:Sayan Mukherjee"
Sayan MukherjeeDuke Universiy, University of Leipzig, Max Planck Institute for Mathematics in the Sciences Verified email at mis.mpg.de Cited by 68569 |
[PDF][PDF] Optimal gene expression analysis by microarrays
DNA microarrays make possible the rapid and comprehensive assessment of the
transcriptional activity of a cell, and as such have proven valuable in assessing the …
transcriptional activity of a cell, and as such have proven valuable in assessing the …
Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles
A Subramanian, P Tamayo… - Proceedings of the …, 2005 - National Acad Sciences
Although genomewide RNA expression analysis has become a routine tool in biomedical
research, extracting biological insight from such information remains a major challenge …
research, extracting biological insight from such information remains a major challenge …
Choosing multiple parameters for support vector machines
The problem of automatically tuning multiple parameters for pattern recognition Support
Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the …
Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the …
Multiclass cancer diagnosis using tumor gene expression signatures
The optimal treatment of patients with cancer depends on establishing accurate diagnoses
by using a complex combination of clinical and histopathological data. In some instances …
by using a complex combination of clinical and histopathological data. In some instances …
[HTML][HTML] Naught all zeros in sequence count data are the same
JD Silverman, K Roche, S Mukherjee… - Computational and …, 2020 - Elsevier
Genomic studies feature multivariate count data from high-throughput DNA sequencing
experiments, which often contain many zero values. These zeros can cause artifacts for …
experiments, which often contain many zero values. These zeros can cause artifacts for …
Feature selection for SVMs
We introduce a method of feature selection for Support Vector Machines. The method is
based upon finding those features which minimize bounds on the leave-one-out error. This …
based upon finding those features which minimize bounds on the leave-one-out error. This …
Nonlinear prediction of chaotic time series using support vector machines
S Mukherjee, E Osuna, F Girosi - Neural Networks for Signal …, 1997 - ieeexplore.ieee.org
A novel method for regression has been recently proposed by Vapnik et al.(1995, 1996).
The technique, called support vector machine (SVM), is very well founded from the …
The technique, called support vector machine (SVM), is very well founded from the …
[HTML][HTML] A genomic strategy to refine prognosis in early-stage non–small-cell lung cancer
A Potti, S Mukherjee, R Petersen… - … England Journal of …, 2006 - Mass Medical Soc
Background Clinical trials have indicated a benefit of adjuvant chemotherapy for patients
with stage IB, II, or IIIA—but not stage IA—non–small-cell lung cancer (NSCLC). This …
with stage IB, II, or IIIA—but not stage IA—non–small-cell lung cancer (NSCLC). This …
An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis
A Sweet-Cordero, S Mukherjee, A Subramanian… - Nature …, 2005 - nature.com
Using advanced gene targeting methods, generating mouse models of cancer that
accurately reproduce the genetic alterations present in human tumors is now relatively …
accurately reproduce the genetic alterations present in human tumors is now relatively …
General conditions for predictivity in learning theory
Developing theoretical foundations for learning is a key step towards understanding
intelligence.'Learning from examples' is a paradigm in which systems (natural or artificial) …
intelligence.'Learning from examples' is a paradigm in which systems (natural or artificial) …