Demo Data from VLDB 2026 / reviewers in the wild / expert
Matthew B. Stocks
dblp:10/8316
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2018
0000-0003-3818-3626ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 2 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
3 papers |
Bioinformatics and computational biology · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › sequence analysis › RNA sequence analysis
microRNA analysis |
0.5 | 2 | 2018 | The UEA sRNA Workbench (version 4.4): a comprehensive suite of tools for analyzing miRNAs and sRNAs · Bioinform. 2018 The UEA sRNA workbench: a suite of tools for analysing and visualizing next generation sequencing microRNA and small RNA datasets · Bioinform. 2012 |
Bioinformatics and computational biology › sequence analysis › RNA sequence analysis
small RNA analysis |
0.5 | 2 | 2018 | The UEA sRNA Workbench (version 4.4): a comprehensive suite of tools for analyzing miRNAs and sRNAs · Bioinform. 2018 The UEA sRNA workbench: a suite of tools for analysing and visualizing next generation sequencing microRNA and small RNA datasets · Bioinform. 2012 |
Bioinformatics and computational biology › transcriptomics › small RNA-seq analysis
small RNA-seq processing |
0.5 | 2 | 2018 | The UEA sRNA Workbench (version 4.4): a comprehensive suite of tools for analyzing miRNAs and sRNAs · Bioinform. 2018 The UEA sRNA workbench: a suite of tools for analysing and visualizing next generation sequencing microRNA and small RNA datasets · Bioinform. 2012 |
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
microRNA prediction |
0.3 | 1 | 2017 | miRCat2: accurate prediction of plant and animal microRNAs from next-generation sequencing datasets · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
workflow · 0.3secondary structure analysis · 0.3entropy-based approach · 0.3next-generation sequencing analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | The UEA sRNA Workbench (version 4.4): a comprehensive suite of tools for analyzing miRNAs and sRNAsabstractMotivation: RNA interference, a highly conserved regulatory mechanism, is mediated via small RNAs (sRNA). Recent technical advances enabled the analysis of larger, complex datasets and the investigation of microRNAs and the less known small interfering RNAs. However, the size and intricacy of current data requires a comprehensive set of tools, able to discriminate the patterns from the low-level, noise-like, variation; numerous and varied suggestions from the community represent an invaluable source of ideas for future tools, the ability of the community to contribute to this software is essential. Results: We present a new version of the UEA sRNA Workbench, reconfigured to allow an easy insertion of new tools/workflows. In its released form, it comprises of a suite of tools in a user-friendly environment, with enhanced capabilities for a comprehensive processing of sRNA-seq data e.g. tools for an accurate prediction of sRNA loci (CoLIde) and miRNA loci (miRCat2), as well as workflows to guide the users through common steps such as quality checking of the input data, normalization of abundances or detection of differential expression represent the first step in sRNA-seq analyses. Availability and implementation: The UEA sRNA Workbench is available at: http://srna-workbench.cmp.uea.ac.uk. The source code is available at: https://github.com/sRNAworkbenchuea/UEA_sRNA_Workbench. Supplementary information: Supplementary data are available at Bioinformatics online. Matthew B. Stocks, Irina Mohorianu, Matthew Beckers, Claudia Paicu, Simon Moxon, Joshua Thody, Tamas Dalmay, Vincent Moulton |
Bioinform. | 1 |
| 2017 | miRCat2: accurate prediction of plant and animal microRNAs from next-generation sequencing datasetsabstractMOTIVATION: MicroRNAs are a class of ∼21-22 nt small RNAs which are excised from a stable hairpin-like secondary structure. They have important gene regulatory functions and are involved in many pathways including developmental timing, organogenesis and development in eukaryotes. There are several computational tools for miRNA detection from next-generation sequencing datasets. However, many of these tools suffer from high false positive and false negative rates. Here we present a novel miRNA prediction algorithm, miRCat2. miRCat2 incorporates a new entropy-based approach to detect miRNA loci, which is designed to cope with the high sequencing depth of current next-generation sequencing datasets. It has a user-friendly interface and produces graphical representations of the hairpin structure and plots depicting the alignment of sequences on the secondary structure. RESULTS: We test miRCat2 on a number of animal and plant datasets and present a comparative analysis with miRCat, miRDeep2, miRPlant and miReap. We also use mutants in the miRNA biogenesis pathway to evaluate the predictions of these tools. Results indicate that miRCat2 has an improved accuracy compared with other methods tested. Moreover, miRCat2 predicts several new miRNAs that are differentially expressed in wild-type versus mutants in the miRNA biogenesis pathway. AVAILABILITY AND IMPLEMENTATION: miRCat2 is part of the UEA small RNA Workbench and is freely available from http://srna-workbench.cmp.uea.ac.uk/. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Claudia Paicu, Irina Mohorianu, Matthew B. Stocks, Aurore Coince, Martina Billmeier, Tamas Dalmay, Vincent Moulton, Simon Moxon |
Bioinform. | 3 |
| 2012 | The UEA sRNA workbench: a suite of tools for analysing and visualizing next generation sequencing microRNA and small RNA datasetsabstractSUMMARY: RNA silencing is a complex, highly conserved mechanism mediated by small RNAs (sRNAs), such as microRNAs (miRNAs), that is known to be involved in a diverse set of biological functions including development, pathogen control, genome maintenance and response to environmental change. Advances in next generation sequencing technologies are producing increasingly large numbers of sRNA reads per sample at a fraction of the cost of previous methods. However, many bioinformatics tools do not scale accordingly, are cumbersome, or require extensive support from bioinformatics experts. Therefore, researchers need user-friendly, robust tools, capable of not only processing large sRNA datasets in a reasonable time frame but also presenting the results in an intuitive fashion and visualizing sRNA genomic features. Herein, we present the UEA sRNA workbench, a suite of tools that is a successor to the web-based UEA sRNA Toolkit, but in downloadable format and with several enhanced and additional features. AVAILABILITY: The program and help pages are available at http://srna-workbench.cmp.uea.ac.uk. CONTACT: [email protected]. Matthew B. Stocks, Simon Moxon, Daniel Mapleson, Hugh C. Woolfenden, Irina Mohorianu, Leighton Folkes, Frank Schwach, Tamas Dalmay, Vincent Moulton |
Bioinform. | 1 |