Author

Gregory C. Gibson

Georgia Institute of Technology

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetics· 3

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Research Focus:GWAS / association mapping· 2 Assay:GWAS summary statistics· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1

Frequent Co-Authors

Alexander TeumeriD· 3 shared Alexis J. BattleiD· 3 shared Anand Kumar AndiappaniD· 3 shared Anette KalnapenkisiD· 3 shared Anke TönjesiD· 3 shared Annique ClaringbouldiD· 3 shared Ashis SahaiD· 3 shared Bernett Teck Kwong LeeiD· 3 shared

Activity by Year

2018-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersGenetics

Alexander TeumerORCID

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3 papers

Recent·Most cited

Mendelian Randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

Eleonora Porcu, Sina Rüeger, Kaido Lepik, Mawussé D. T. Agbessi, Habibul Ahsan, Isabel Alves, Anand Kumar Andiappan, Wibowo Arindrarto, Philip Awadalla, Alexis J. Battle, Frank Beutner, Marc Jan Bonder, Dorret Irene Boomsma, Mark W. Christiansen, Annique Claringbould, , René Luijk

This paper introduces TWMR, a Mendelian Randomization method that identifies gene-trait associations by integrating GWAS and eQTL data, revealing 3,913 novel associations across 43 human phenotypes.

Nature Communications · Jul 24, 2019Peer-reviewedGenetics

Novel susceptibility loci and genetic regulation mechanisms for type 2 diabetes

Angli Xue, Yang Wu, Zhihong Zhu, Futao Zhang, Kathryn E. Kemper, Zhili Zheng, Loïc Yengo, Luke R. Lloyd‐Jones, Julia Sidorenko, Yeda Wu, Mawussé D. T. Agbessi, Habibul Ahsan, Isabel Alves, Anand Kumar Andiappan, Philip Awadalla, , Jian Yang

This study identifies 139 common and 4 rare genetic variants associated with type 2 diabetes through GWAS and integrates gene expression and epigenomic data to highlight potential functional genes and regulatory mechanisms.

Nature Communications · Jul 23, 2018Peer-reviewedGenetics

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Ting Qi, Yang Wu, Jian Zeng, Futao Zhang, Angli Xue, Longda Jiang, Zhihong Zhu, Kathryn E. Kemper, Loïc Yengo, Zhili Zheng, Mawussé D. T. Agbessi, Habibul Ahsan, Isabel Alves, Anand Kumar Andiappan, Philip Awadalla, , Jian Yang

The paper identifies gene targets for brain-related traits using transcriptomic and methylomic data from blood, finding strong correlations between genetic effects in brain and blood tissues.

Nature Communications · Jun 5, 2018Peer-reviewedGenetics