Demo Data from EDBT 2026 / reviewers in the wild / expert
Jonathan D. Moore
dblp:14/7109
· DBLP profile ↗
4ranked-venue papers
2as first author
0since 2021 · last 2013
0000-0002-5486-0407ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 4 · 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
2 papers |
Bioinformatics and computational biology · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
gene expression analysis |
0.2 | 1 | 2013 | MEME-LaB: motif analysis in clusters · Bioinform. 2013 |
Bioinformatics and computational biology › sequence analysis › motif discovery
motif analysis |
0.2 | 1 | 2013 | MEME-LaB: motif analysis in clusters · Bioinform. 2013 |
Bioinformatics and computational biology › gene regulation
transcription factor binding site prediction |
0.2 | 1 | 2013 | MEME-LaB: motif analysis in clusters · Bioinform. 2013 |
Bioinformatics and computational biology › sequence alignment
local alignment |
0.1 | 1 | 2008 | TreeMos: a high-throughput phylogenomic approach to find and visualize phylogenetic mosaicism · Bioinform. 2008 |
Bioinformatics and computational biology › phylogenetics
phylogenomics |
0.1 | 1 | 2008 | TreeMos: a high-throughput phylogenomic approach to find and visualize phylogenetic mosaicism · Bioinform. 2008 |
Bioinformatics and computational biology
sequence alignment |
0.1 | 1 | 2008 | TreeMos: a high-throughput phylogenomic approach to find and visualize phylogenetic mosaicism · Bioinform. 2008 |
Methods — techniques the papers use, named apart from their topics
web interface · 0.2ab initio motif finding · 0.2sliding window · 0.1local alignment · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | MEME-LaB: motif analysis in clustersabstractSUMMARY: Genome-wide expression analysis can result in large numbers of clusters of co-expressed genes. Although there are tools for ab initio discovery of transcription factor-binding sites, most do not provide a quick and easy way to study large numbers of clusters. To address this, we introduce a web tool called MEME-LaB. The tool wraps MEME (an ab initio motif finder), providing an interface for users to input multiple gene clusters, retrieve promoter sequences, run motif finding and then easily browse and condense the results, facilitating better interpretation of the results from large-scale datasets. AVAILABILITY: MEME-LaB is freely accessible at: http://wsbc.warwick.ac.uk/wsbcToolsWebpage/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Paul Brown, Laura Baxter, Richard Hickman, Jim Beynon, Jonathan D. Moore, Sascha Ott |
Bioinform. | 5 |
| 2012 | MCMC-ODPR: Primer design optimization using Markov Chain Monte Carlo samplingabstractBACKGROUND: Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly. We aimed to develop a system that would implement primer reuse to design degenerate primers that could be designed around SNPs, thus find the fewest necessary primers and the lowest cost whilst maintaining an acceptable coverage and provide a cost effective solution. We have implemented Metropolis-Hastings Markov Chain Monte Carlo for optimizing primer reuse. We call it the Markov Chain Monte Carlo Optimized Degenerate Primer Reuse (MCMC-ODPR) algorithm. RESULTS: After repeating the program 1020 times to assess the variance, an average of 17.14% fewer primers were found to be necessary using MCMC-ODPR for an equivalent coverage without implementing primer reuse. The algorithm was able to reuse primers up to five times. We compared MCMC-ODPR with single sequence primer design programs Primer3 and Primer-BLAST and achieved a lower primer cost per amplicon base covered of 0.21 and 0.19 and 0.18 primer nucleotides on three separate gene sequences, respectively. With multiple sequences, MCMC-ODPR achieved a lower cost per base covered of 0.19 than programs BatchPrimer3 and PAMPS, which achieved 0.25 and 0.64 primer nucleotides, respectively. CONCLUSIONS: MCMC-ODPR is a useful tool for designing primers at various melting temperatures at good target coverage. By combining degeneracy with optimal primer reuse the user may increase coverage of sequences amplified by the designed primers at significantly lower costs. Our analyses showed that overall MCMC-ODPR outperformed the other primer-design programs in our study in terms of cost per covered base. James L. Kitchen, Jonathan D. Moore, Sarah A. Palmer, Robin G. Allaby |
BMC Bioinform. | 2 |
| 2008 | TreeMos: a high-throughput phylogenomic approach to find and visualize phylogenetic mosaicismabstractSUMMARY: TreeMos is a novel high-throughput graphical analysis application that allows the user to search for phylogenetic mosaicism among one or more DNA or protein sequence multiple alignments and additional unaligned sequences. TreeMos uses a sliding window and local alignment algorithm to identify the nearest neighbour of each sequence segment, and visualizes instances of sequence segments whose nearest neighbour is anomalous to that identified using the global alignment. Data sets can include whole genome sequences allowing phylogenomic analyses in which mosaicism may be attributed to recombination between any two points in the genome. TreeMos can be run from the command line, or within a web browser allowing the relationships between taxa to be explored by drill-through. AVAILABILITY: http://www2.warwick.ac.uk/fac/sci/whri/research/archaeobotany. Jonathan D. Moore, Robin G. Allaby |
Bioinform. | 1 |
| 2008 | CWRML: representing crop wild relative conservation and use data in XMLabstractBACKGROUND: Crop wild relatives are wild species that are closely related to crops. They are valuable as potential gene donors for crop improvement and may help to ensure food security for the future. However, they are becoming increasingly threatened in the wild and are inadequately conserved, both in situ and ex situ. Information about the conservation status and utilisation potential of crop wild relatives is diverse and dispersed, and no single agreed standard exists for representing such information; yet, this information is vital to ensure these species are effectively conserved and utilised. The European Community-funded project, European Crop Wild Relative Diversity Assessment and Conservation Forum, determined the minimum information requirements for the conservation and utilisation of crop wild relatives and created the Crop Wild Relative Information System, incorporating an eXtensible Markup Language (XML) schema to aid data sharing and exchange. RESULTS: Crop Wild Relative Markup Language (CWRML) was developed to represent the data necessary for crop wild relative conservation and ensure that they can be effectively utilised for crop improvement. The schema partitions data into taxon-, site-, and population-specific elements, to allow for integration with other more general conservation biology schemata which may emerge as accepted standards in the future. These elements are composed of sub-elements, which are structured in order to facilitate the use of the schema in a variety of crop wild relative conservation and use contexts. Pre-existing standards for data representation in conservation biology were reviewed and incorporated into the schema as restrictions on element data contents, where appropriate. CONCLUSION: CWRML provides a flexible data communication format for representing in situ and ex situ conservation status of individual taxa as well as their utilisation potential. The development of the schema highlights a number of instances where additional standards-development may be valuable, particularly with regard to the representation of population-specific data and utilisation potential. As crop wild relatives are intrinsically no different to other wild plant species there is potential for the inclusion of CWRML data elements in the emerging standards for representation of biodiversity data. Jonathan D. Moore, Shelagh P. Kell, Jose M. Iriondo, Brian V. Ford-Lloyd, Nigel Maxted |
BMC Bioinform. | 1 |