Demo Data from EDBT 2026 / reviewers in the wild / expert
Sara R. Selitsky
dblp:170/4529
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2016
0000-0001-8765-5269ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
immunoinformatics |
0.2 | 1 | 2016 | Assembly-based inference of B-cell receptor repertoires from short read RNA sequencing data with V'DJer · Bioinform. 2016 |
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis |
0.1 | 1 | 2016 | Assembly-based inference of B-cell receptor repertoires from short read RNA sequencing data with V'DJer · Bioinform. 2016 |
Bioinformatics and computational biology › transcriptomics
transcript assembly |
0.1 | 1 | 2016 | Assembly-based inference of B-cell receptor repertoires from short read RNA sequencing data with V'DJer · Bioinform. 2016 |
Methods — techniques the papers use, named apart from their topics
sequence assembly · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Assembly-based inference of B-cell receptor repertoires from short read RNA sequencing data with V'DJerabstractMOTIVATION: B-cell receptor (BCR) repertoire profiling is an important tool for understanding the biology of diverse immunologic processes. Current methods for analyzing adaptive immune receptor repertoires depend upon PCR amplification of VDJ rearrangements followed by long read amplicon sequencing spanning the VDJ junctions. While this approach has proven to be effective, it is frequently not feasible due to cost or limited sample material. Additionally, there are many existing datasets where short-read RNA sequencing data are available but PCR amplified BCR data are not. RESULTS: We present here V'DJer, an assembly-based method that reconstructs adaptive immune receptor repertoires from short-read RNA sequencing data. This method captures expressed BCR loci from a standard RNA-seq assay. We applied this method to 473 Melanoma samples from The Cancer Genome Atlas and demonstrate V'DJer's ability to accurately reconstruct BCR repertoires from short read mRNA-seq data. AVAILABILITY AND IMPLEMENTATION: V'DJer is implemented in C/C ++, freely available for academic use and can be downloaded from Github: https://github.com/mozack/vdjer CONTACT: [email protected] or [email protected] information: Supplementary data are available at Bioinformatics online. Lisle E. Mose, Sara R. Selitsky, Lisa M. Bixby, David L. Marron, Michael D. Iglesia, Jonathan S. Serody, Charles M. Perou, Benjamin Vincent, Joel S. Parker |
Bioinform. | 2 |
| 2015 | tDRmapper: challenges and solutions to mapping, naming, and quantifying tRNA-derived RNAs from human small RNA-sequencing dataabstractBACKGROUND: Small RNA-sequencing has revealed the diversity and high abundance of small RNAs derived from tRNAs, referred to as tRNA-derived RNAs. However, at present, there is no standardized nomenclature and there are no methods for accurate annotation and quantification of these small RNAs. tRNA-derived RNAs have unique features that limit the utility of conventional alignment tools and quantification methods. RESULTS: We describe here the challenges of mapping, naming, and quantifying tRNA-derived RNAs and present a novel method that addresses them, called tDRmapper. We then use tDRmapper to perform a comparative analysis of tRNA-derived RNA profiles across different human cell types and diseases. We found that (1) tRNA-derived RNA profiles can differ dramatically across different cell types and disease states, (2) that positions and types of chemical modifications of tRNA-derived RNAs vary by cell type and disease, and (3) that entirely different tRNA-derived RNA species can be produced from the same parental tRNA depending on the cell type. CONCLUSION: tDRmappernot only provides a standardized nomenclature and quantification scheme, but also includes graphical visualization that facilitates the discovery of novel tRNA and tRNA-derived RNA biology. Sara R. Selitsky, Praveen Sethupathy |
BMC Bioinform. | 1 |