Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Saket Navlakha"'
Projecting COVID-19 disease severity in cancer patients using purposefully-designed machine learning
Publikováno v:
BMC Infectious Diseases, Vol 21, Iss 1, Pp 1-8 (2021)
BMC Infectious Diseases
BMC Infectious Diseases
Background Accurately predicting outcomes for cancer patients with COVID-19 has been clinically challenging. Numerous clinical variables have been retrospectively associated with disease severity, but the predictive value of these variables, and how
Autor:
Saket Navlakha, Illia Ziamtsov
Publikováno v:
Bioinformatics (Oxford, England). 36(12)
Motivation Developing methods to efficiently analyze 3D point cloud data of plant architectures remain challenging for many phenotyping applications. Here, we describe a tool that tackles four core phenotyping tasks: classification of cloud points in
Autor:
Saket Navlakha
Publikováno v:
Neural Computation. 29:287-312
Networks have become instrumental in deciphering how information is processed and transferred within systems in almost every scientific field today. Nearly all network analyses, however, have relied on humans to devise structural features of networks
Autor:
Illia Ziamtsov, Saket Navlakha
Publikováno v:
Plant physiology. 181(4)
Developing automated methods to efficiently process large volumes of point cloud data remains a challenge for three-dimensional (3D) plant phenotyping applications. Here, we describe the development of machine learning methods to tackle three primary
Publikováno v:
Journal of Computational Biology. 16:253-264
The division of a protein interaction network into biologically meaningful modules can aid with automated detection of protein complexes and prediction of biological processes and can uncover the global organization of the cell. We propose the use of
Publikováno v:
PLoS Computational Biology, Vol 11, Iss 7, p e1004347 (2015)
PLoS Computational Biology
PLoS Computational Biology
Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly us
Autor:
Carl Kingsford, Saket Navlakha
Publikováno v:
Bioinformatics
Motivation: Understanding the association between genetic diseases and their causal genes is an important problem concerning human health. With the recent influx of high-throughput data describing interactions between gene products, scientists have b
Publikováno v:
Algorithms for Molecular Biology : AMB
Algorithms for Molecular Biology, Vol 7, Iss 1, p 25 (2012)
Algorithms for Molecular Biology, Vol 7, Iss 1, p 25 (2012)
Background Understanding the evolution of biological networks can provide insight into how their modular structure arises and how they are affected by environmental changes. One approach to studying the evolution of these networks is to reconstruct p