4.6 Article

Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification

Related references

Note: Only part of the references are listed.
Article Computer Science, Information Systems

Hidden Markov models for cancer classification using gene expression profiles

Thanh Nguyen et al.

INFORMATION SCIENCES (2015)

Review Genetics & Heredity

Methods of integrating data to uncover genotype-phenotype interactions

Marylyn D. Ritchie et al.

NATURE REVIEWS GENETICS (2015)

Article Computer Science, Interdisciplinary Applications

A simulation to analyze feature selection methods utilizing gene ontology for gene expression classification

Christopher E. Gillies et al.

JOURNAL OF BIOMEDICAL INFORMATICS (2013)

Editorial Material Computer Science, Information Systems

Making it personal: translational bioinformatics

Atul J. Butte et al.

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2013)

Article Biochemical Research Methods

Matrix eQTL: ultra fast eQTL analysis via large matrix operations

Andrey A. Shabalin

BIOINFORMATICS (2012)

Article Biochemistry & Molecular Biology

Annotation of functional variation in personal genomes using RegulomeDB

Alan P. Boyle et al.

GENOME RESEARCH (2012)

Article Computer Science, Interdisciplinary Applications

Synergistic effect of different levels of genomic data for cancer clinical outcome prediction

Dokyoon Kim et al.

JOURNAL OF BIOMEDICAL INFORMATICS (2012)

Editorial Material Computer Science, Information Systems

The coming age of data-driven medicine: translational bioinformatics' next frontier

Nigam H. Shah et al.

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2012)

Article Biochemistry & Molecular Biology

Co-clustering phenome-genome for phenotype classification and disease gene discovery

TaeHyun Hwang et al.

NUCLEIC ACIDS RESEARCH (2012)

Article Biochemistry & Molecular Biology

An Integrated Approach to Uncover Drivers of Cancer

Uri David Akavia et al.

Article Oncology

DNA Microarrays Are Predictive of Cancer Prognosis: A Re-evaluation

Xiaohui Fan et al.

CLINICAL CANCER RESEARCH (2010)

Article Biochemical Research Methods

Graph sharpening plus graph integration: a synergy that improves protein functional classification

Hyunjung Shin et al.

BIOINFORMATICS (2007)

Article Biochemical Research Methods

A statistical framework for genomic data fusion

GRG Lanckriet et al.

BIOINFORMATICS (2004)

Article Biochemical Research Methods

Predicting HIV drug resistance with neural networks

S Draghici et al.

BIOINFORMATICS (2003)

Article Multidisciplinary Sciences

Gene expression profiling predicts clinical outcome of breast cancer

LJ van't Veer et al.

NATURE (2002)

Article Genetics & Heredity

A general test of association for quantitative traits in nuclear families

GR Abecasis et al.

AMERICAN JOURNAL OF HUMAN GENETICS (2000)