Advanced search    

Search: authors:"Ross D. King"

21 papers found.
Use AND, OR, NOT, +word, -word, "long phrase", (parentheses) to fine-tune your search.

A Tool for Multiple Targeted Genome Deletions that Is Precise, Scar-Free, and Suitable for Automation

Many advances in synthetic biology require the removal of a large number of genomic elements from a genome. Most existing deletion methods leave behind markers, and as there are a limited number of markers, such methods can only be applied a fixed number of times. Deletion methods that recycle markers generally are either imprecise (remove untargeted sequences), or leave scar ...

The Use of Weighted Graphs for Large-Scale Genome Analysis

There is an acute need for better tools to extract knowledge from the growing flood of sequence data. For example, thousands of complete genomes have been sequenced, and their metabolic networks inferred. Such data should enable a better understanding of evolution. However, most existing network analysis methods are based on pair-wise comparisons, and these do not scale to ...

EXACT2: the semantics of biomedical protocols

Background The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is ...

An investigation into the population abundance distribution of mRNAs, proteins, and metabolites in biological systems

Motivation: Distribution analysis is one of the most basic forms of statistical analysis. Thanks to improved analytical methods, accurate and extensive quantitative measurements can now be made of the mRNA, protein and metabolite from biological systems. Here, we report a large-scale analysis of the population abundance distributions of the transcriptomes, proteomes and metabolomes ...

On the formalization and reuse of scientific research

Ross D. King Maria Liakata Chuan Lu Stephen G. Oliver Larisa N. Soldatova 0 Department of Biochemistry, Cambridge Systems Biology Centre, University of Cambridge , Sanger Building, 80 Tennis Court

Functional Expression of Parasite Drug Targets and Their Human Orthologs in Yeast

Background The exacting nutritional requirements and complicated life cycles of parasites mean that they are not always amenable to high-throughput drug screening using automated procedures. Therefore, we have engineered the yeast Saccharomyces cerevisiae to act as a surrogate for expressing anti-parasitic targets from a range of biomedically important pathogens, to facilitate the ...

An ontology of scientific experiments

Larisa N Soldatova 0 Ross D King 0 0 The University of Wales , Aberystwyth, Penglais, Ceredigion SY23 3DB, UK Receive free email alerts when new articles cite this article - sign up in the box at ... scientific experiments Larisa N. Soldatova* and Ross D. King The formal description of experiments for efficient analysis, annotation and sharing of results is a fundamental part of the practice of science

The EXACT description of biomedical protocols

Motivation: Many published manuscripts contain experiment protocols which are poorly described or deficient in information. This means that the published results are very hard or impossible to repeat. This problem is being made worse by the increasing complexity of high-throughput/automated methods. There is therefore a growing need to represent experiment protocols in an efficient ...

Locational distribution of gene functional classes in Arabidopsis thaliana

Michael C Riley 0 Amanda Clare 0 Ross D King 0 0 Address: Department of Computer Science, University of Wales , Aberystwyth, Penglais, Aberystwyth, Ceredigion, SY23 3DB, Wales , UK Background: We

Homology Induction: the use of machine learning to improve sequence similarity searches

approach of HI is applicable to all sequence based homology search methods. Additional material Additional File Acknowledgments Andreas Karwath and Ross D. King were supported by the EPSRC grant GR/L62849

Machine learning of functional class from phenotype data

Amanda Clare 0 Ross D. King 0 0 Department of Computer Science, University of Wales , Aberystwyth SY23 3DB , UK Motivation: Mutant phenotype growth experiments are an important novel source of

An ontology for a Robot Scientist

Motivation: A Robot Scientist is a physically implemented robotic system that can automatically carry out cycles of scientific experimentation. We are commissioning a new Robot Scientist designed to investigate gene function in S. cerevisiae. This Robot Scientist will be capable of initiating >1,000 experiments, and making >200,000 observations a day. Robot Scientists provide a ...

Towards Robot Scientists for autonomous scientific discovery

We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical ...

On the use of qualitative reasoning to simulate and identify metabolic pathways

Motivation: Perhaps the greatest challenge of modern biology is to develop accurate in silico models of cells. To do this we require computational formalisms for both simulation (how according to the model the state of the cell evolves over time) and identification (learning a model cell from observation of states). We propose the use of qualitative reasoning (QR) as a unified ...

Confirmation of data mining based predictions of protein function

Ross D. King 0 Paul H. Wise 0 Amanda Clare 0 0 Department of Computer Science, University of Wales , Aberystwyth, Wales, SY23 3DB, UK Motivation: A central problem in bioinformatics is the

Application of metabolomics to plant genotype discrimination using statistics and machine learning

Motivation: Metabolomics is a post genomic technology which seeks to provide a comprehensive profile of all the metabolites present in a biological sample. This complements the mRNA profiles provided by microarrays, and the protein profiles provided by proteomics. To test the power of metabolome analysis we selected the problem of discrimating between related genotypes of ...

The utility of different representations of protein sequence for predicting functional class

Motivation: Data Mining Prediction (DMP) is a novel approach to predicting protein functional class from sequence. DMP works even in the absence of a homologous protein of known function. We investigate the utility of different ways of representing protein sequence in DMP (residue frequencies, phylogeny, predicted structure) using the Escherichia coli genome as a model. Results: ...

Statistical evaluation of the Predictive Toxicology Challenge 2000–2001

Motivation: The development of in silico models to predict chemical carcinogenesis from molecular structure would help greatly to prevent environmentally caused cancers. The Predictive Toxicology Challenge (PTC) competition was organized to test the state-of-the-art in applying machine learning to form such predictive models. Results: Fourteen machine learning groups generated 111 ...

Further developments towards a genome-scale metabolic model of yeast

Background To date, several genome-scale network reconstructions have been used to describe the metabolism of the yeast Saccharomyces cerevisiae, each differing in scope and content. The recent community-driven reconstruction, while rigorously evidenced and well annotated, under-represented metabolite transport, lipid metabolism and other pathways, and was not amenable to ...