| scholarly article | Q13442814 |
| P2093 | author name string | Chris Gaiteri | |
| Bruce Hoff | |||
| Elias Chaibub Neto | |||
| Hiroyoshi Toyoshiba | |||
| Shinya Tasaki | |||
| Ben Sauerwine | |||
| P2860 | cites work | Variations in DNA elucidate molecular networks that cause disease | Q24622333 |
| Beyond modules and hubs: the potential of gene coexpression networks for investigating molecular mechanisms of complex brain disorders | Q26830010 | ||
| Network-based analysis of affected biological processes in type 2 diabetes models | Q28469240 | ||
| Harnessing naturally randomized transcription to infer regulatory relationships among genes | Q28755546 | ||
| An integrative genomics approach to infer causal associations between gene expression and disease | Q29616385 | ||
| A general framework for weighted gene co-expression network analysis | Q29617580 | ||
| Increasing the power to detect causal associations by combining genotypic and expression data in segregating populations | Q31109293 | ||
| Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks | Q31159122 | ||
| Genetic networks of liver metabolism revealed by integration of metabolic and transcriptional profiling | Q33325905 | ||
| Using genetic markers to orient the edges in quantitative trait networks: the NEO software | Q33328317 | ||
| High-resolution mapping of expression-QTLs yields insight into human gene regulation | Q33375030 | ||
| A Bayesian framework to account for complex non-genetic factors in gene expression levels greatly increases power in eQTL studies | Q33576696 | ||
| Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals. | Q33637547 | ||
| Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks | Q33725093 | ||
| Gene expression network reconstruction by convex feature selection when incorporating genetic perturbations | Q33769760 | ||
| High-confidence discovery of genetic network regulators in expression quantitative trait loci data | Q33787812 | ||
| Overlap of expression quantitative trait loci (eQTL) in human brain and blood | Q33789101 | ||
| Simulating systems genetics data with SysGenSIM | Q33954156 | ||
| Patterns of cis regulatory variation in diverse human populations | Q34244935 | ||
| CAUSAL GRAPHICAL MODELS IN SYSTEMS GENETICS: A UNIFIED FRAMEWORK FOR JOINT INFERENCE OF CAUSAL NETWORK AND GENETIC ARCHITECTURE FOR CORRELATED PHENOTYPES | Q34473049 | ||
| A Bayesian framework for inference of the genotype-phenotype map for segregating populations | Q34760494 | ||
| Integrative modeling of eQTLs and cis-regulatory elements suggests mechanisms underlying cell type specificity of eQTLs | Q34917186 | ||
| Learning gene networks under SNP perturbations using eQTL datasets | Q35105560 | ||
| Gene network inference via structural equation modeling in genetical genomics experiments | Q36515885 | ||
| Modeling causality for pairs of phenotypes in system genetics | Q36643803 | ||
| Inferring causal phenotype networks from segregating populations | Q36724284 | ||
| Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease | Q36914722 | ||
| Mapping cis- and trans-regulatory effects across multiple tissues in twins | Q37200482 | ||
| The pleiotropic structure of the genotype-phenotype map: the evolvability of complex organisms. | Q37844408 | ||
| Type 2 diabetes, APOE gene, and the risk for dementia and related pathologies: The Honolulu-Asia Aging Study | Q43935519 | ||
| Integrative genomics identifies APOE ε4 effectors in Alzheimer's disease | Q47942475 | ||
| Genetical genomics: the added value from segregation. | Q52133626 | ||
| Benefits of fatty fish on dementia risk are stronger for those without APOE epsilon4. | Q53273541 | ||
| Topological and causal structure of the yeast transcriptional regulatory network | Q77985187 | ||
| P433 | issue | 4 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | Bayesian network | Q812540 |
| P304 | page(s) | 973-989 | |
| P577 | publication date | 2015-01-28 | |
| P1433 | published in | Genetics | Q3100575 |
| P1476 | title | Bayesian network reconstruction using systems genetics data: comparison of MCMC methods | |
| P478 | volume | 199 |
| Q57740664 | A molecular network of the aging human brain provides insights into the pathology and cognitive decline of Alzheimer’s disease |
| Q60043959 | An integrative approach for building personalized gene regulatory networks for precision medicine |
| Q90467617 | Genetic risk for Alzheimer's dementia predicts motor deficits through multi-omic systems in older adults |
| Q28596011 | Genetic variants in Alzheimer disease - molecular and brain network approaches |
| Q92539404 | High-Dimensional Bayesian Network Inference From Systems Genetics Data Using Genetic Node Ordering |
| Q93089768 | Inferring Interaction Networks From Multi-Omics Data |
| Q58793079 | Multi-omic Directed Networks Describe Features of Gene Regulation in Aged Brains and Expand the Set of Genes Driving Cognitive Decline |
| Q31133613 | New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data |
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