Skip to main navigation
Skip to search
Skip to main content
Princeton University Home
Help & FAQ
Home
Profiles
Research units
Facilities
Projects
Research output
Search by expertise, name or affiliation
Context-sensitive data integration and prediction of biological networks
Chad L. Myers,
Olga G. Troyanskaya
Computer Science
Lewis-Sigler Institute for Integrative Genomics
Princeton Institute for Computational Science and Engineering
Center for Statistics & Machine Learning
Research output
:
Contribution to journal
›
Article
›
peer-review
87
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Context-sensitive data integration and prediction of biological networks'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Mathematics
Assignment
14%
Bayesian Approach
15%
Biological Networks
84%
Context
38%
Data Integration
100%
Demonstrate
9%
Dependent
10%
Functional Genomics
27%
Gene
15%
Genomics
36%
High Throughput
21%
Knowledge
11%
Modeling
10%
Prediction
49%
Query
15%
Recovery
15%
Relevance
15%
Saccharomyces Cerevisiae
24%
Scenarios
14%
Specificity
18%
Vary
13%
Medicine & Life Sciences
Bayes Theorem
25%
Biological Phenomena
60%
Datasets
32%
Genes
8%
Information Storage and Retrieval
18%
Noise
19%
Saccharomyces cerevisiae
19%
Sensitivity and Specificity
15%
Technology
13%
Engineering & Materials Science
Data integration
70%
Genes
14%
Recovery
10%
Throughput
10%
Yeast
18%