@article{BishopPhysicaD, author = "Bishop MJ, Bub G, Garny A, Gavaghan D, Rodriguez B", journal = "Physica D", title = "An investigation into the role of the optical detection set-up in the recording of cardiac optical mapping signals: a Monte Carlo simulation study.", year = "2009", } @inproceedings{GeometricSNP, abstract = "A common type of DNA variation is called a Single Nucleotide Polymorphism (SNP), where a single position within a DNA sequence is altered from one nucleotide base to another. The problem of identifying disease-associated SNPs has been the subject of extensive research by statisticians. However, less research has been done within the computing community. In this paper, we propose a novel geometrical computing model for the SNP Motif Identification Problem. The purpose of our research is to explore the properties of SNPs in a combinatorial way. We test our algorithm on two real clinical datasets, and give computational results which demonstrate the efficiency and effectiveness of our approach.", author = "Gaofeng Huang and Peter Jeavons", booktitle = "Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2007", doi = "10.1109/BIBE.2007.4375593", isbn = "978-1-4244-1509-0 ", pages = "395-402", title = "A Geometrical Model for the SNP Motif Identification Problem", url = "http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=4375593", year = "2007", } @inproceedings{ExactHeuristicSNP, abstract = "A Single Nucleotide Polymorphism (SNP) is a small DNA variation which occurs naturally between different individuals of the same species. Some combinations of SNPs in the human genome are known to increase the risk of certain complex genetic diseases. This paper formulates the problem of identifying such disease-associated SNP motifs as a combinatorial optimization problem and shows it to be NP-hard. Both exact and heuristic approaches for this problem are developed and tested on simulated data and real clinical data. Computational results are given to demonstrate that these approaches are sufficiently effective to support ongoing biological research.", author = "Gaofeng Huang and Peter Jeavons and Dominic Kwiatkowski", booktitle = "Proceedings of 5th Asia-Pacific Bioinformatics Conference, APBC 2007", isbn = "978-1-86094-783-4", pages = "175-184", publisher = "Imperial College Press", series = "Advances in Bioinformatics and Computational Biology", title = "Exact and Heuristic Approaches for Identifying Disease-Associated SNP Motifs", volume = "5", year = "2007", } @article{EnhancingBindingSitePrediction, abstract = "A problem faced by many algorithms for finding transcription factor (TF) binding sites is the high number of false positive hits that result with the increased sensitivity of their prediction. A main contributing factor to this is the short and degenerate nature of these sites which results in a low signal-to-noise ratio. In order to counter this problem, one needs to look beyond the assumption that individual bases of a TF binding site act independently from each other when binding to a transcription factor. In this paper, we present a new method based on templates, designed to exploit the discriminatory features, nucleotide polymorphism, and structural homology present in TF binding sites for distinguishing them from nonbinding sites.", author = "S. Gunewardena, P. Jeavons, Z. Zhang", doi = "10.1089/cmb.2006.13.929", journal = "Journal of Computational Biology", number = "4", pages = "929-945", title = "Enhancing the prediction of transcription factor binding sites by incorporating structural properties and nucleotide covariations", url = "http://www.liebertonline.com/doi/abs/10.1089/cmb.2006.13.929", volume = "13", year = "2006", } @article{OperonMycobacteriumBovis, abstract = "Mycobacterium bovis BCG and Mycobacterium tuberculosis possess a single arylamine N-acetyltransferase whose gene is predicted to occur within a six-gene operon. Deletion of the nat gene caused an extended lag phase in M. bovis BCG and a cell morphology associated with an altered pattern of cell wall mycolates. Analysis of cDNA from M. bovis BCG shows that during in vitro growth all the genes in the putative nat operon are expressed and the open reading frames are contiguous, supporting the existence of an operon. Two genes in the operon, Mb3599c and Mb3600c, are predicted to encode homologues of enzymes annotated as a 2,3-dihydroxybiphenyl 1,2-dioxygenase (bphC5) and a 2-hydroxy-6-oxo-6-phenylhexa-2,4-dienoate hydrolase (bphD2), respectively, in Rhodococcus RHA1. As predicted, M. bovis BCG cell lysates metabolized the BphC substrate 2,3-dihydroxybiphenyl (2,3-DHB) to 2-hydroxy-6-oxo-6-phenylhexa-2,4-dienoic acid (HOPDA), a BphD substrate, which was subsequently hydrolysed. Immunoprecipitation of the BphD homologue from these lysates led to an accumulation of HOPDA. M. bovis BCG growth on both solid and liquid media was inhibited with either 2,3-DHB or an inhibitor of BphC, 3-chlorocatechol (3-CC). In addition, incubation with 2,3-DHB affects the lipid composition of the cell wall resulting in a diminished level of mycolates and an altered cell morphology similar to the Δnat strain. We propose the enzymes encoded by the putative operon have a similar endogenous role to that of the NAT enzyme and are part of a pathway important for cell wall synthesis.", author = "M. Anderton, S. Bhakta, G. Besra, P. Jeavons, L. Eltis, E. Sim ", doi = "10.1111/j.1365-2958.2005.04945.x", journal = "Molecular Microbiology", number = "1", pages = "181-192", title = "Characterization of the putative operon containing arylamine N-acetyltransferase (nat) in Mycobacterium bovis BCG", url = "http://www.blackwell-synergy.com/doi/abs/10.1111/j.1365-2958.2005.04945.x", volume = "59", year = "2006", } @techreport{RR-05-03, abstract = "A Single Nucleotide Polymorphism (SNP) is a small DNA variation which occurs naturally between different individuals of the same species. Some combinations of SNPs in the human genome are known to increase the risk of certain complex genetic diseases. This paper formulates the problem of identifying such disease-associated SNP motifs as a combinatorial optimization problem and shows it to be mathcal-hard. Both exact and heuristic approaches for this problem are developed and tested on simulated data and real clinical data. Computational results indicate that our algorithms are efficient AI tools which can support ongoing biological research.", author = "Gaofeng Huang and Peter Jeavons and Dominic Kwiatkowski", institution = "Oxford University Computing Laboratory", month = "July", number = "RR-05-03", title = "Exact and Heuristic Approaches for Identifying Disease-Associated SNP Motifs", year = "2005", } @techreport{RR-04-24, abstract = "This is a two-part report. In the first part we introduce the reader to biological sequence alignment. We discus dynamic programming as is used in sequence alignment, first in the case of two sequences and later, how it is adopted for multiple sequence alignment. Several references are given to the different sequence alignment strategies reported in the literature used to enhance the standard dynamic programming algorithm for sequence alignment to suit biological sequences. A short discussion on how alignments are scored is given. Finally, some of the existing sequence alignment tools are described.

The second part of this report presents a critical analysis of information as it relates to biological sequence alignment. Information relating to the sequences being aligned form the basis on which any alignment is built. In its basic form this information might quantify how individual residues are scored when aligned with each other or how gaps are scored when introduced between two residues. Every biological sequence has if not explicit, at least some form of implicit information relating to its residues that form distinguishing markers along the sequence. There are many ways of extracting this information such as from databases of the relevant sequences, from the literature, prior processing etc. It is reasonable to assume that the more sequence information we use in an alignment, the more confidant we can be of the resulting alignment, and hence make better hypothesis of the unknown sequences. The aim of this part of the report is to build a framework on how to represent this information in such a way as to facilitate the dynamic and flexible incorporation of it to facilitate sequence alignments.

", author = "Sumedha Gunewardena and Peter Jeavons", institution = "Oxford University Computing Laboratory", month = "November", number = "RR-04-24", title = "Information categorisation in biological sequence alignments", year = "2004", } @techreport{RR-03-21, abstract = "A problem faced by many algorithms for finding transcription factor binding sites is the high number of false positive hits that result with the increased sensitivity of their prediction. A main contributing factor to this is the short and degenerate nature of these sites which results in a low signal to noise ratio. In order to counter this problem one needs to look beyond the base independence assumption. We propose a model based on templates designed to capture not only the vertical consensus but also the correlation of individual bases with the other bases of the site.", author = "Sumedha Gunewardena and Peter Jeavons", institution = "Oxford University Computing Laboratory", month = "October", number = "RR-03-21", title = "Finding transcription factor binding sites in DNA Sequences: A template based approach", year = "2003", } @article{AgaroseGelImage, abstract = "Motivation: Automatic tools to speed up routine biological processes are very much sought after in bio-medical research. Much repetitive work in molecular biology, such as allele calling in genetic analysis, can be made semi-automatic or task specific automatic by using existing techniques from computer science and signal processing. Computerized analysis is reproducible and avoids various forms of human error. Semi-automatic techniques with an interactive check on the results speed up the analysis and reduce the error. Results: We have successfully implemented an image processing software package to automatically analyze agarose gel images of polymorphic DNA markers. We have obtained up to 90% accuracy for the classification of alleles in good quality images and up to 70% accuracy in average quality images. These results are obtained within a few seconds. Even after subsequent interactive checking to increase the accuracy of allele classification to 100%, the overall speed with which the data can be processed is greatly increased, compared to manual allele classification.", author = "P. S. Umesh Adiga, A. Bhomra, M. G. Turri, A. Nicod, S. R. Datta, Peter Jeavons, Richard Mott, Jonathan Flint", journal = "Bioinformatics", number = "11", pages = "1084-1089", title = "Automatic analysis of agarose gel images", url = "http://bioinformatics.oxfordjournals.org/cgi/content/abstract/17/11/1084", volume = "17", year = "2001", }