Author

Dmitri S. Pavlichin

Stanford Medicine

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

Biology Disciplines

Click to filter author papers

Bioinformatics· 2 Genomics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 3 Approach:statistical model· 3 Assay:whole-genome sequencing· 3 Research Focus:variant calling· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Hanlee P. JiiD· 3 shared HoJoon LeeiD· 3 shared Stephanie GreeriD· 2 shared Tsachy WeissmaniD· 2 shared Ahmed Shuaibi· 1 shared Bo ZhouiD· 1 shared Chris HughesiD· 1 shared John BelliD· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 24 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersBioinformatics

Hanlee P. JiORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

The Human Pangenome's sequence conservation reveals a landscape of polymorphic structural variations

HoJoon Lee, Stephanie Greer, Dmitri S. Pavlichin, Chris Hughes, Bo Zhou, Tsachy Weissman, Hanlee P. Ji

The paper analyzes the Human Pangenome to identify conserved and polymorphic structural variations across diverse haploid assemblies.

bioRxiv · Oct 6, 2022 · PreprintGenomics

KmerKeys: a web resource for searching indexed genome assemblies and variants

Dmitri S. Pavlichin, HoJoon Lee, Stephanie Greer, Susan M. Grimes, Tsachy Weissman, Hanlee P. Ji

KmerKeys provides a web tool for efficient k-mer-based querying of genome assemblies and variant databases.

Nucleic Acids Research · Apr 21, 2022Peer-reviewedBioinformatics

Unique K-mer sequences for validating cancer-related substitution, insertion and deletion mutations

HoJoon Lee, Ahmed Shuaibi, John Bell, Dmitri S. Pavlichin, Hanlee P. Ji

The paper develops a method using k-mer sequences to validate somatic mutations in cancer genome sequencing data, showing it effectively identifies true positive mutations including insertions and deletions.

NAR Cancer · Dec 1, 2020Peer-reviewedBioinformatics