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Genetics

D-Index
66
Citations
24210
World Ranking
2578
National Ranking
1145

Overview

Bogdan Pasaniuc is affiliated with the University of California, Los Angeles, United States. Their research focuses primarily on Biochemistry, Genetics, and Molecular Biology, with a strong emphasis on Genetics and Molecular Biology subfields. Other areas of study include Pulmonary and Respiratory Medicine, Cancer Research, and Infectious Diseases.

Their scientific contributions encompass a range of topics, notably Genetic Associations and Epidemiology, Genetic Mapping and Diversity in Plants and Animals, and Bioinformatics and Genomic Networks. Additional topics include Genetic and phenotypic traits in livestock, Epigenetics and DNA Methylation, BRCA gene mutations in cancer, and Prostate Cancer Treatment and Research.

Pasaniuc has published extensively in a variety of academic venues. Frequent publication outlets include bioRxiv (Cold Spring Harbor Laboratory), The American Journal of Human Genetics, Nature Genetics, UNC Libraries, and Nature Communications.

They have collaborated with several co-authors, including Kangcheng Hou, Yi Ding, Arjun Bhattacharya, Ruth Johnson, and Tommer Schwarz, indicating active participation in research networks.

Selected recent papers by Bogdan Pasaniuc include:

  • Mapping the human genetic architecture of COVID-19, 2021, Nature
  • Prostate cancer reactivates developmental epigenomic programs during metastatic progression, 2020, Nature Genetics
  • Polygenic scoring accuracy varies across the genetic ancestry continuum, 2023, Nature
  • Principles and methods for transferring polygenic risk scores across global populations, 2023, Nature Reviews Genetics
  • Broad transcriptomic dysregulation occurs across the cerebral cortex in ASD, 2022, Nature

Best Publications

  • Integrative approaches for large-scale transcriptome-wide association studies.

    Alexander Gusev;Alexander Gusev;Arthur Ko;Huwenbo Shi;Gaurav Bhatia;Gaurav Bhatia

  • Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

    Bjarni J. Vilhjálmsson;Jian Yang;Hilary K. Finucane;Alexander Gusev

  • Leveraging Polygenic Functional Enrichment to Improve GWAS Power

    Gleb Kichaev;Gaurav Bhatia;Po Ru Loh;Steven Gazal;Steven Gazal

  • Colocalization of GWAS and eQTL Signals Detects Target Genes

    Farhad Hormozdiari;Martijn van de Bunt;Martijn van de Bunt;Ayellet V. Segrè;Xiao Li

  • Opportunities and challenges for transcriptome-wide association studies.

    Michael Wainberg;Nasa Sinnott-Armstrong;Nicholas Mancuso;Alvaro N. Barbeira

  • Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases

    Alexander Gusev;S. Hong Lee;Gosia Trynka;Hilary Finucane

  • Integrating Functional Data to Prioritize Causal Variants in Statistical Fine-Mapping Studies

    Gleb Kichaev;Wen-Yun Yang;Sara Lindstrom;Farhad Hormozdiari

  • Identifying causal variants at loci with multiple signals of association.

    Farhad Hormozdiari;Emrah Kostem;Eun Yong Kang;Bogdan Pasaniuc

  • Dissecting the genetics of complex traits using summary association statistics

    Bogdan Pasaniuc;Alkes L. Price

  • Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights

    Alexander Gusev;Alexander Gusev;Nicholas Mancuso;Hyejung Won;Maria Kousi

  • Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits

    Noah Zaitlen;Phillip L. Kraft;Phillip L. Kraft;Nick Patterson;Bogdan Pasaniuc

  • Contrasting the Genetic Architecture of 30 Complex Traits from Summary Association Data.

    Huwenbo Shi;Gleb Kichaev;Bogdan Pasaniuc

  • Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

    Bogdan Pasaniuc;Bogdan Pasaniuc;Nadin Rohland;Nadin Rohland;Paul J. McLaren;Paul J. McLaren;Kiran Garimella

  • Probabilistic fine-mapping of transcriptome-wide association studies.

    Nicholas Mancuso;Malika K Freund;Ruth Johnson;Huwenbo Shi

  • Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits

    Nicholas Mancuso;Huwenbo Shi;Pagé Goddard;Gleb Kichaev

  • Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits

    Huwenbo Shi;Nicholas Mancuso;Sarah Spendlove;Bogdan Pasaniuc

  • A Bayesian framework for multiple trait colocalization from summary association statistics.

    Claudia Giambartolomei;Jimmy Zhenli Liu;Wen Zhang;Mads Hauberg;Mads Hauberg

  • Fast and accurate inference of local ancestry in Latino populations

    Yael Baran;Bogdan Pasaniuc;Bogdan Pasaniuc;Sriram Sankararaman;Sriram Sankararaman;Dara G. Torgerson

  • Genetic Control of Expression and Splicing in Developing Human Brain Informs Disease Mechanisms.

    Rebecca L. Walker;Gokul Ramaswami;Christopher Hartl;Nicholas Mancuso

  • Fast and accurate imputation of summary statistics enhances evidence of functional enrichment

    Bogdan Pasaniuc;Noah Zaitlen;Huwenbo Shi;Gaurav Bhatia

Frequent Co-Authors

Alexander Gusev
Alexander Gusev Dana-Farber Cancer Institute
Alkes L. Price
Alkes L. Price Harvard University
Noah Zaitlen
Noah Zaitlen University of California, Los Angeles
Christopher A. Haiman
Christopher A. Haiman University of Southern California
Matthew L. Freedman
Matthew L. Freedman Harvard University
Peter Kraft
Peter Kraft Harvard University
David Reich
David Reich Harvard Medical School
Eran Halperin
Eran Halperin University of California, Los Angeles
Eleazar Eskin
Eleazar Eskin University of California, Los Angeles
Sara Lindström
Sara Lindström University of Washington

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