Demo Data from EDBT 2026 / reviewers in the wild / expert
Arnab Pain
dblp:90/7429
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2015
0000-0002-1755-2819ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 4
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
3 papers |
Bioinformatics and computational biology · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › genomics › genome visualization
genomic variant visualization |
0.2 | 1 | 2014 | SVAMP: sequence variation analysis, maps and phylogeny · Bioinform. 2014 |
Bioinformatics and computational biology
phylogenetics |
0.2 | 1 | 2014 | SVAMP: sequence variation analysis, maps and phylogeny · Bioinform. 2014 |
Bioinformatics and computational biology › genomics › structural variation
structural variation analysis |
0.1 | 1 | 2009 | SnoopCGH: software for visualizing comparative genomic hybridization data · Bioinform. 2009 |
Bioinformatics and computational biology › genomics
genomic variant analysis |
0.1 | 1 | 2014 | SVAMP: sequence variation analysis, maps and phylogeny · Bioinform. 2014 |
Parallel and multicore computing › parallel computing › parallel bioinformatics
parallel sequence analysis |
0.0 | 1 | 2013 | READSCAN: a fast and scalable pathogen discovery program with accurate genome relative abundance estimation · Bioinform. 2013 |
Methods — techniques the papers use, named apart from their topics
parallel computing · 0.3principal coordinate analysis · 0.2visualization · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | PhyTB: Phylogenetic tree visualisation and sample positioning for M. tuberculosisabstractBACKGROUND: Phylogenetic-based classification of M. tuberculosis and other bacterial genomes is a core analysis for studying evolutionary hypotheses, disease outbreaks and transmission events. Whole genome sequencing is providing new insights into the genomic variation underlying intra- and inter-strain diversity, thereby assisting with the classification and molecular barcoding of the bacteria. One roadblock to strain investigation is the lack of user-interactive solutions to interrogate and visualise variation within a phylogenetic tree setting. RESULTS: We have developed a web-based tool called PhyTB ( http://pathogenseq.lshtm.ac.uk/phytblive/index.php ) to assist phylogenetic tree visualisation and identification of M. tuberculosis clade-informative polymorphism. Variant Call Format files can be uploaded to determine a sample position within the tree. A map view summarises the geographical distribution of alleles and strain-types. The utility of the PhyTB is demonstrated on sequence data from 1,601 M. tuberculosis isolates. CONCLUSION: PhyTB contextualises M. tuberculosis genomic variation within epidemiological, geographical and phylogenic settings. Further tool utility is possible by incorporating large variants and phenotypic data (e.g. drug-resistance profiles), and an assessment of genotype-phenotype associations. Source code is available to develop similar websites for other organisms ( http://sourceforge.net/projects/phylotrack ). Ernest D. Benavente, Francesc Coll, Nick Furnham, Ruth McNerney, Judith R. Glynn, Susana G. Campino, Arnab Pain, Fady R. Mohareb, Taane G. Clark |
BMC Bioinform. | 7 |
| 2014 | SVAMP: sequence variation analysis, maps and phylogenyabstractSUMMARY: SVAMP is a stand-alone desktop application to visualize genomic variants (in variant call format) in the context of geographical metadata. Users of SVAMP are able to generate phylogenetic trees and perform principal coordinate analysis in real time from variant call format (VCF) and associated metadata files. Allele frequency map, geographical map of isolates, Tajima's D metric, single nucleotide polymorphism density, GC and variation density are also available for visualization in real time. We demonstrate the utility of SVAMP in tracking a methicillin-resistant Staphylococcus aureus outbreak from published next-generation sequencing data across 15 countries. We also demonstrate the scalability and accuracy of our software on 245 Plasmodium falciparum malaria isolates from three continents. AVAILABILITY AND IMPLEMENTATION: The Qt/C++ software code, binaries, user manual and example datasets are available at http://cbrc.kaust.edu.sa/svamp CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Raeece Naeem, Lailatul Hidayah, Mark D. Preston, Taane G. Clark, Arnab Pain |
Bioinform. | 5 |
| 2013 | READSCAN: a fast and scalable pathogen discovery program with accurate genome relative abundance estimationabstractAbstract Summary: READSCAN is a highly scalable parallel program to identify non-host sequences (of potential pathogen origin) and estimate their genome relative abundance in high-throughput sequence datasets. READSCAN accurately classified human and viral sequences on a 20.1 million reads simulated dataset in <27 min using a small Beowulf compute cluster with 16 nodes (Supplementary Material). Availability: http://cbrc.kaust.edu.sa/readscan Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. Raeece Naeem, Mamoon Rashid 0003, Arnab Pain |
Bioinform. | 3 |
| 2009 | SnoopCGH: software for visualizing comparative genomic hybridization dataabstractUNLABELLED: Array-based comparative genomic hybridization (CGH) technology is used to discover and validate genomic structural variation, including copy number variants, insertions, deletions and other structural variants (SVs). The visualization and summarization of the array CGH data outputs, potentially across many samples, is an important process in the identification and analysis of SVs. We have developed a software tool for SV analysis using data from array CGH technologies, which is also amenable to short-read sequence data. AVAILABILITY AND IMPLEMENTATION: SnoopCGH is written in java and is available from http://snoopcgh.sourceforge.net/ Jacob Almagro-Garcia, Magnus Manske, Celine Carret, Susana G. Campino, Sarah Auburn, Bronwyn L. MacInnis, Gareth Maslen, Arnab Pain, Christopher I. Newbold, Dominic Kwiatkowski, Taane G. Clark |
Bioinform. | 8 |