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Connection

Riyan Cheng to Animals

This is a "connection" page, showing publications Riyan Cheng has written about Animals.
Connection Strength

0.246
  1. Practical considerations regarding the use of genotype and pedigree data to model relatedness in the context of genome-wide association studies. G3 (Bethesda). 2013 Oct 03; 3(10):1861-7.
    View in: PubMed
    Score: 0.026
  2. The heritability of oxycodone reward and concomitant phenotypes in a LG/J?×?SM/J mouse advanced intercross line. Addict Biol. 2014 Jul; 19(4):552-61.
    View in: PubMed
    Score: 0.024
  3. Genetic determinants for intramuscular fat content and water-holding capacity in mice selected for high muscle mass. Mamm Genome. 2011 Oct; 22(9-10):530-43.
    View in: PubMed
    Score: 0.022
  4. Genome-wide association studies and the problem of relatedness among advanced intercross lines and other highly recombinant populations. Genetics. 2010 Jul; 185(3):1033-44.
    View in: PubMed
    Score: 0.020
  5. Genome-Wide Association Study of Age-Related Hearing Loss in CFW Mice Identifies Multiple Genes and Loci, Including Prkag2. J Assoc Res Otolaryngol. 2025 Aug; 26(4):409-426.
    View in: PubMed
    Score: 0.014
  6. Genetic Loci Influencing Cue-Reactivity in Heterogeneous Stock Rats. Genes Brain Behav. 2025 Apr; 24(2):e70018.
    View in: PubMed
    Score: 0.014
  7. A cost-effective, high-throughput, highly accurate genotyping method for outbred populations. G3 (Bethesda). 2025 Feb 05; 15(2).
    View in: PubMed
    Score: 0.014
  8. Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks. Cell Rep. 2023 08 29; 42(8):112873.
    View in: PubMed
    Score: 0.013
  9. An exponential increase in QTL detection with an increased sample size. Genetics. 2023 05 26; 224(2).
    View in: PubMed
    Score: 0.013
  10. Genome-Wide Association Study in 3,173 Outbred Rats Identifies Multiple Loci for Body Weight, Adiposity, and Fasting Glucose. Obesity (Silver Spring). 2020 10; 28(10):1964-1973.
    View in: PubMed
    Score: 0.010
  11. Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity. G3 (Bethesda). 2020 03 05; 10(3):951-965.
    View in: PubMed
    Score: 0.010
  12. Genome-wide Associations Reveal Human-Mouse Genetic Convergence and Modifiers of Myogenesis, CPNE1 and STC2. Am J Hum Genet. 2019 12 05; 105(6):1222-1236.
    View in: PubMed
    Score: 0.010
  13. Hnrnph1 Is A Quantitative Trait Gene for Methamphetamine Sensitivity. PLoS Genet. 2015 Dec; 11(12):e1005713.
    View in: PubMed
    Score: 0.007
  14. Quantitative trait locus mapping methods for diversity outbred mice. G3 (Bethesda). 2014 Sep 18; 4(9):1623-33.
    View in: PubMed
    Score: 0.007
  15. Discovery and refinement of muscle weight QTLs in B6 × D2 advanced intercross mice. Physiol Genomics. 2014 Aug 15; 46(16):571-82.
    View in: PubMed
    Score: 0.007
  16. QTLs for murine red blood cell parameters in LG/J and SM/J F(2) and advanced intercross lines. Mamm Genome. 2012 Jun; 23(5-6):356-66.
    View in: PubMed
    Score: 0.006
  17. High-resolution genetic mapping using the Mouse Diversity outbred population. Genetics. 2012 Feb; 190(2):437-47.
    View in: PubMed
    Score: 0.006
  18. Genome-wide association for fear conditioning in an advanced intercross mouse line. Behav Genet. 2012 May; 42(3):437-48.
    View in: PubMed
    Score: 0.006
  19. Genome-wide association for methamphetamine sensitivity in an advanced intercross mouse line. Genes Brain Behav. 2012 Feb; 11(1):52-61.
    View in: PubMed
    Score: 0.006
  20. Fine-mapping alleles for body weight in LG/J × SM/J F2 and F(34) advanced intercross lines. Mamm Genome. 2011 Oct; 22(9-10):563-71.
    View in: PubMed
    Score: 0.006
  21. Fine mapping of QTL for prepulse inhibition in LG/J and SM/J mice using F(2) and advanced intercross lines. Genes Brain Behav. 2010 Oct; 9(7):759-67.
    View in: PubMed
    Score: 0.005
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.