Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Sumitra Mohan

dblp:244/9093 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2019
0009-0008-1702-1429ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
cancer genomics
0.412019
In silico error correction improves cfDNA mutation calling · Bioinform. 2019
Bioinformatics and computational biology › cancer genomics
circulating tumor DNA analysis
0.412019
In silico error correction improves cfDNA mutation calling · Bioinform. 2019
Bioinformatics and computational biology › sequence analysis
sequencing error correction
0.112019
In silico error correction improves cfDNA mutation calling · Bioinform. 2019

Methods — techniques the papers use, named apart from their topics

redundancy-based error correction · 0.4
YearPublicationVenuePosition
2019 In silico error correction improves cfDNA mutation calling
abstract
MOTIVATION: Circulating-free DNA (cfDNA) profiling by sequencing is an important minimally invasive protocol for monitoring the mutation profile of solid tumours in cancer patients. Since the concentration of available cfDNA is limited, sample library generation relies on multiple rounds of PCR amplification, during which the accumulation of errors results in reduced sensitivity and lower accuracy. RESULTS: We present PCR Error Correction (PEC), an algorithm to identify and correct errors in short read sequencing data. It exploits the redundancy that arises from multiple rounds of PCR amplification. PEC is particularly well suited to applications such as single-cell sequencing and circulating tumour DNA (ctDNA) analysis, in which many cycles of PCR are used to generate sufficient DNA for sequencing from small amounts of starting material. When applied to ctDNA analysis, PEC significantly improves mutation calling accuracy, achieving similar levels of performance to more complex strategies that require additional protocol steps and access to calibration DNA datasets. AVAILABILITY AND IMPLEMENTATION: PEC is available under the GPL-v3 Open Source licence, and is freely available from: https://github.com/CRUKMI-ComputationalBiology/PCR_Error_Correction.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Chang Sik Kim, Sumitra Mohan, Mahmood Ayub, Dominic G. Rothwell, Caroline Dive, Ged Brady, Crispin J. Miller
Bioinform.2