Dr Amanda Clare

BA (Oxon), MSc( Edinburgh), PhD

Dr Amanda Clare

Senior Lecturer

Department of Computer Science

Contact Details

Profile

My research is in data analysis and data science, and in particular in bioinformatics and natural language processing/text analysis, but also the analysis of sequences in general, including time series. I am interested in all genomics questions and in particular, in what we can do with computers (algorithms, data structures and artificial intelligence) to help answer these questions. DNA/RNA sequencing allows us to inspect the genetic composition of microbes, animals, plants and viruses, but after we have obtained the sequences, what can we learn? How are communities changing over time? How are enzymes within a community specialised for different roles? How can we detect genes in communities of organisms that have never been cultured? I'm also interested in the ethical and moral implications of genomic technologies, and in how the public will react to this information.

Teaching

Research

My research is in data analysis and data science, and in particular in bioinformatics and natural language processing/text analysis, but also the analysis of sequences in general, including time series. I am interested in all aspects of bioinformatics. Recent areas have included genomics and metagenomics, gene-finding, primer design, genome modification. I have a background in machine learning and data mining, particularly in the construction and interpretation of explanatory models. I also collaborate with text mining researchers to analyse the structure of science and scientific publications.

Research Groups

Publications

Ravenscroft, J, Arie, C, Clare, A, Dagan, I & Liakata, M 2021, 'CD2CR: Co-reference Resolution Across Documents and Domains', Paper presented at European Chapter of the Association for Computational Linguistics 2021, 19 Apr 2021. <https://arxiv.org/abs/2101.12637>
Dimonaco, N, Aubrey, W, Kenobi, K, Clare, A & Creevey, C 2021 'No one tool to rule them all: Prokaryotic gene prediction tool performance is highly dependent on the organism of study' bioRxiv. https://doi.org/10.1101/2021.05.21.445150
Major, L, Clare, A, Daykin, J, Mora, B, Peña Gamboa, L & Zarges, C 2020, Evaluation of a Permutation-Based Evolutionary Framework for Lyndon Factorizations. in T Bäck, M Preuss, A Deutz, H Wang, C Doerr, M Emmerich & H Trautmann (eds), Parallel Problem Solving from Nature – PPSN XVI: 16th International Conference, Leiden, The Netherlands, September 5-9, 2020, Proceedings. Lecture Notes in Computer Science, vol. 12269, Springer Nature, pp. 390-403, Parallel Problem Solving Nature, Leiden, Netherlands, 05 Sep 2020. https://doi.org/10.1007/978-3-030-58112-1_27
Ravenscroft, J, Clare, A & Liakata, M 2020 'Measuring prominence of scientific work in online news as a proxy for impact' arXiv. <https://arxiv.org/abs/2007.14454>
Nicholls, S, Aubrey, W, de Grave, K, Schietgat, L, Creevey, C & Clare, A 2020, 'On the complexity of haplotyping a microbial community', Bioinformatics, vol. N/A, no. N/A, btaa977, pp. 1-7. https://doi.org/10.1101/2020.08.10.244848, https://doi.org/10.1093/bioinformatics/btaa977
More publications on the Research Portal