Review and big data perspectives on robust data mining approaches for industrial process modeling with outliers and missing data
Industrial process data are usually mixed with missing data and outliers which can greatly
affect the statistical explanation abilities for traditional data-driven modeling methods. In this …
affect the statistical explanation abilities for traditional data-driven modeling methods. In this …
Bayesian non-parametric hidden Markov models with applications in genomics
We propose a flexible non-parametric specification of the emission distribution in hidden
Markov models and we introduce a novel methodology for carrying out the computations …
Markov models and we introduce a novel methodology for carrying out the computations …
Parent-specific copy number in paired tumor–normal studies using circular binary segmentation
AB Olshen, H Bengtsson, P Neuvial… - …, 2011 - academic.oup.com
Motivation: High-throughput techniques facilitate the simultaneous measurement of DNA
copy number at hundreds of thousands of sites on a genome. Older techniques allow …
copy number at hundreds of thousands of sites on a genome. Older techniques allow …
A sequential approach to market state modeling and analysis in online p2p lending
Online peer-to-peer (P2P) lending is an emerging wealth-management service for
individuals, which allows lenders to directly bid and invest on the listings created by …
individuals, which allows lenders to directly bid and invest on the listings created by …
Recruitment market trend analysis with sequential latent variable models
Recruitment market analysis provides valuable understanding of industry-specific economic
growth and plays an important role for both employers and job seekers. With the rapid …
growth and plays an important role for both employers and job seekers. With the rapid …
Time-dependence of graph theory metrics in functional connectivity analysis
Brain graphs provide a useful way to computationally model the network structure of the
connectome, and this has led to increasing interest in the use of graph theory to quantitate …
connectome, and this has led to increasing interest in the use of graph theory to quantitate …
Bayesian hierarchical structured variable selection methods with application to molecular inversion probe studies in breast cancer
L Zhang, V Baladandayuthapani… - Journal of the Royal …, 2014 - academic.oup.com
The analysis of genomics alterations that may occur in nature when segments of
chromosomes are copied (known as copy number alterations) has been a focus of research …
chromosomes are copied (known as copy number alterations) has been a focus of research …
Epilepsy as a dynamic disease: A Bayesian model for differentiating seizure risk from natural variability
Objective A fundamental challenge in treating epilepsy is that changes in observed seizure
frequencies do not necessarily reflect changes in underlying seizure risk. Rather, changes in …
frequencies do not necessarily reflect changes in underlying seizure risk. Rather, changes in …
Bayesian random segmentation models to identify shared copy number aberrations for array CGH data
Array-based comparative genomic hybridization (aCGH) is a high-resolution, high-
throughput technique for studying the genetic basis of cancer. The resulting data consist of …
throughput technique for studying the genetic basis of cancer. The resulting data consist of …
Computational methods for identification of recurrent copy number alteration patterns by array CGH
SP Shah - Cytogenetic and genome research, 2009 - karger.com
Recurrent DNA copy number alterations (CNA) are widely studied in diagnostic and
cytogenetic cancer research. CNAs reveal locations that may alter gene dosage and thus …
cytogenetic cancer research. CNAs reveal locations that may alter gene dosage and thus …