Bogdan Pasaniuc
Genetics · 2011–2021
A researcher in the Science corpus: 14 papers; trusts 35 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Genetics — 309 citations into it; #1,621 of 6,854 by trust here, #477 by citations
- Molecular Biology — 178 citations into it
- Epidemiology — 20 citations into it
- Artificial Intelligence — 18 citations into it
- Statistics and Probability — 17 citations into it
- Plant Science — 15 citations into it
- Computer Vision and Pattern Recognition — 14 citations into it
- Optimization & Training — 11 citations into it
Whom Bogdan Pasaniuc trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tomaz Berisa
- Jian Yang
- Karen N. Conneely
- Joseph K. Pickrell
- Jonathan Marchini
- Naomi R. Wray
- Michael Boehnke
- Sang Hong Lee
- Seunggeun Lee
- Michael E. Goddard
Who trusts Bogdan Pasaniuc overall
Papers from Bogdan Pasaniuc's perspective
Ordered by how strongly the researchers Bogdan Pasaniuc trusts endorse each paper. Same corpus, a different order for every researcher.
- Regression Shrinkage and Selection via the Lasso
- Common SNPs explain a large proportion of heritability for human height (Nature Genetics)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- The Elements of Statistical Learning
- The NHGRI GWAS Catalog, a curated resource of SNP-trait associations
- Potential etiologic and functional implications of genome-wide association loci for human diseases and traits (Proceedings of the National Academy of Sciences of the United States of America)
- 10 Years of GWAS Discovery: Biology, Function, and Translation. (American Journal of Human Genetics)
- Genome-partitioning of genetic variation for complex traits using common SNPs (Nature Genetics)
- Accuracy of Predicting the Genetic Risk of Disease Using a Genome-Wide Approach (PLoS ONE)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Their papers
- Integrative approaches for large-scale transcriptome-wide association studies (2015) — 2,212 citations
- Biological Sequence Modeling with Convolutional Kernel Networks (2017) — 178 citations
- Colocalization of GWAS and eQTL Signals Detects Target Genes (2016) — 671 citations
- Opportunities and challenges for transcriptome-wide association studies (2019) — 757 citations
- Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores (2015) — 1,263 citations
- Dissecting the genetics of complex traits using summary association statistics (2016) — 418 citations
- Extremely low-coverage sequencing and imputation increases power for genome-wide association studies (2012) — 257 citations
- Mapping the human genetic architecture of COVID-19 (2021) — 807 citations
- Leveraging polygenic functional enrichment to improve GWAS power (2017) — 843 citations
- Probabilistic fine-mapping of transcriptome-wide association studies (2017) — 370 citations
- Integrating Functional Data to Prioritize Causal Variants in Statistical Fine-Mapping Studies (2014) — 492 citations
- Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. (2014) — 595 citations
- Identifying Causal Variants at Loci with Multiple Signals of Association (2014) — 468 citations
- New approaches to disease mapping in admixed populations (2011) — 170 citations