Dr. Katherine James

Research Associate

A wealth of biological data has been produced in the past decades. However, these data are spread over hundreds of diverse databases and are heterogeneous in nature. My research focuses on the systematic integration of these data in order to characterise highly complex cellular systems and infer new knowledge from the data experimentally.

I am currently researching the biological fingerprints of fatigue using primary Sjögren’s syndrome (pSS) as a disease model.

My previous projects have involved investigating the response to oxidative stress in Saccharomyces cerevisiae using probabilistic functional integrated networks, the systems biology of single nucleotide polymorphisms in Bacillus subtilis and the link between genotype and clinical phenotype in the bacterium Staphylococcus aureus.

Protein Network Image

Research Interests

  • Systems biology and integrative bioinformatics
  • Probabilistic functional integrated networks
  • Comparative genomics
  • Molecular biology of Staphylococcus aureus, Saccharomyces cerevisiae and Bacillus subtilis
  • Microarray analysis
  • Biomarker detection


  • A. Best, K. James, C. Dalgliesh, E. Hong, M. Kheirolahi-Kouhestani, T. Curk, Y. Xu, M. Danilenko, R. Hussain, B. Keavney, A. Wipat, R. Klinck, I. Cowell, K. Cheong Lee, C. Austin, J. Venables, B. Chabot, M. Koref, A. Tyson-Capper, and D. Elliott, “Human tra2 proteins jointly control a chek1 splicing switch amongst alternative and constitutive target exons,” Nature communications, vol. [in press], 2014.
    author = {Best, A and James, K and Dalgliesh, C and Hong, E and Kheirolahi-Kouhestani, M and Curk, T and Xu, Y and Danilenko, M and Hussain, R and Keavney, B and Wipat, A and Klinck, R and Cowell, I and Cheong Lee, K and Austin, C and Venables, JP and Chabot, B and Koref, MS and Tyson-Capper, A and Elliott, DJ},
    title = {Human Tra2 proteins jointly control a CHEK1 splicing switch amongst alternative and constitutive target exons},
    journal = {Nature Communications},
    year = {2014},
    volume = {[in press]}
  • [DOI] G. Misirli, A. Wipat, J. Mullen, K. James, M. Pocock, W. Smith, N. Allenby, and J. S. Hallinan, “Bacillondex: an integrated data resource for systems and synthetic biology,” J integr bioinform, vol. 10, iss. 2, pp. 224-224, 2013.
    author = {Misirli, G and Wipat, A and Mullen, J and James, K and Pocock, M
    and Smith, W and Allenby, N and Hallinan, J S},
    title = {BacillOndex: An Integrated Data Resource for Systems and Synthetic
    journal = {J Integr Bioinform},
    year = {2013},
    volume = {10},
    pages = {224-224},
    number = {2},
    abstract = {BacillOndex is an extension of the Ondex data integration system,
    providing a semantically annotated, integrated knowledge base for
    the model Gram-positive bacterium Bacillus subtilis. This application
    allows a user to mine a variety of B. subtilis data sources, and
    analyse the resulting integrated dataset, which contains data about
    genes, gene products and their interactions. The data can be analysed
    either manually, by browsing using Ondex, or computationally via
    a Web services interface. We describe the process of creating a BacillOndex
    instance, and describe the use of the system for the analysis of
    single nucleotide polymorphisms in B. subtilis Marburg. The Marburg
    strain is the progenitor of the widely-used laboratory strain B.
    subtilis 168. We identified 27 SNPs with predictable phenotypic effects,
    including genetic traits for known phenotypes. We conclude that BacillOndex
    is a valuable tool for the systems-level investigation of, and hypothesis
    generation about, this important biotechnology workhorse. Such understanding
    contributes to our ability to construct synthetic genetic circuits
    in this organism.},
    doi = {10.2390/biecoll-jib-2013-224},
    owner = {n8384838},
    pmid = {23571273},
    timestamp = {2013.05.09},
    url = {http://www.hubmed.org/display.cgi?uids=23571273}
  • [DOI] J. Weile, K. James, J. Hallinan, S. J. Cockell, P. Lord, A. Wipat, and D. J. Wilkinson, “Bayesian integration of networks without gold standards,” Bioinformatics, vol. 28, iss. 11, pp. 1495-1500, 2012.
    author = {Weile, J and James, K and Hallinan, J and Cockell, S J and Lord,
    P and Wipat, A and Wilkinson, D J},
    title = {Bayesian integration of networks without gold standards},
    journal = {Bioinformatics},
    year = {2012},
    volume = {28},
    pages = {1495-1500},
    number = {11},
    month = {Jun},
    abstract = {Biological experiments give insight into networks of processes inside
    a cell, but are subject to error and uncertainty. However, due to
    the overlap between the large number of experiments reported in public
    databases it is possible to assess the chances of individual observations
    being correct. In order to do so, existing methods rely on high-quality
    'gold standard' reference networks, but such reference networks are
    not always available.We present a novel algorithm for computing the
    probability of network interactions that operates without gold standard
    reference data. We show that our algorithm outperforms existing gold
    standard-based methods. Finally, we apply the new algorithm to a
    large collection of genetic interaction and protein-protein interaction
    experiments.The integrated dataset and a reference implementation
    of the algorithm as a plug-in for the Ondex data integration framework
    are available for download at http://bio-nexus.ncl.ac.uk/projects/nogold/},
    doi = {10.1093/bioinformatics/bts154},
    owner = {n8384838},
    pmid = {22492647},
    timestamp = {2013.05.09},
    url = {http://www.hubmed.org/display.cgi?uids=22492647}
  • [DOI] K. James, A. Wipat, and J. Hallinan, “Is newer better?–evaluating the effects of data curation on integrated analyses in \textit\Saccharomyces cerevisiae,” Integr biol (camb), vol. 4, iss. 7, pp. 715-727, 2012.
    author = {James, K and Wipat, A and Hallinan, J},
    title = {Is newer better?--evaluating the effects of data curation on integrated
    analyses in \textit{\{S}accharomyces cerevisiae}},
    journal = {Integr Biol (Camb)},
    year = {2012},
    volume = {4},
    pages = {715-727},
    number = {7},
    month = {Jul},
    abstract = {Recent high-throughput experiments have produced a wealth of heterogeneous
    datasets, each of which provides information about different aspects
    of the cell. Consequently, integration of diverse data types is essential
    in order to address many biological questions. The quality of any
    integrated analysis system is dependent upon the quality of its component
    data, and upon the Gold Standard data used to evaluate it. It is
    commonly assumed that the quality of data improves as databases grow
    and change, particularly for manually curated databases. However,
    the validity of this assumption can be questioned, given the constant
    changes in the data coupled with the high level of noise associated
    with high-throughput experimental techniques. One of the most powerful
    approaches to data integration is the use of Probabilistic Functional
    Integrated Networks (PFINs). Here, we systematically analyse the
    changes in four highly-curated and widely-used online databases and
    evaluate the extent to which these changes affect the protein function
    prediction performance of PFINs in the yeast Saccharomyces cerevisiae.
    We find that the global trend in network performance improves over
    time. Where individual areas of biology are concerned, however, the
    most recent files do not always produce the best results. Individual
    datasets have unique biases towards different biological processes
    and by selecting and integrating relevant datasets performance can
    be improved. When using any type of integrated system to answer a
    specific biological question careful selection of raw data and Gold
    Standard is vital, since the most recent data may not be the most
    doi = {10.1039/c2ib00123c},
    owner = {n8384838},
    pmid = {22526920},
    timestamp = {2013.05.09},
    url = {http://www.hubmed.org/display.cgi?uids=22526920}
  • K. James, S. J. Lycett, A. Wipat, and J. S. Hallinan, “Multiple gold standards address bias in functional network integration,” 2011.
    author = {James, K. and Lycett, S. J. and Wipat, A. and Hallinan, J. S.},
    title = {Multiple gold standards address bias in functional network integration},
    year = {2011},
    journal = {Newcastle University Technical Report Series},
    owner = {n8384838},
    timestamp = {2013.03.07},
    volume = {TR1302}
  • [DOI] J. S. Hallinan, K. James, and A. Wipat, “Network approaches to the functional analysis of microbial proteins,” Adv microb physiol, vol. 59, pp. 101-133, 2011.
    author = {Hallinan, J S and James, K and Wipat, A},
    title = {Network approaches to the functional analysis of microbial proteins},
    journal = {Adv Microb Physiol},
    year = {2011},
    volume = {59},
    pages = {101-133},
    abstract = {Large amounts of detailed biological data have been generated over
    the past few decades. Much of these data is freely available in over
    1000 online databases; an enticing, but frustrating resource for
    microbiologists interested in a systems-level view of the structure
    and function of microbial cells. The frustration engendered by the
    need to trawl manually through hundreds of databases in order to
    accumulate information about a gene, protein, pathway, or organism
    of interest can be alleviated by the use of computational data integration
    to generated network views of the system of interest. Biological
    networks can be constructed from a single type of data, such as protein-protein
    binding information, or from data generated by multiple experimental
    approaches. In an integrated network, nodes usually represent genes
    or gene products, while edges represent some form of interaction
    between the nodes. Edges between nodes may be weighted to represent
    the probability that the edge exists in vivo. Networks may also be
    enriched with ontological annotations, facilitating both visual browsing
    and computational analysis via web service interfaces. In this review,
    we describe the construction, analysis of both single-data source
    and integrated networks, and their application to the inference of
    protein function in microbes.},
    doi = {10.1016/B978-0-12-387661-4.00005-7},
    owner = {n8384838},
    pmid = {22114841},
    timestamp = {2013.05.09},
    url = {http://www.hubmed.org/display.cgi?uids=22114841}
  • [DOI] A. Lister, V. Charoensawan, S. De, K. James, S C. Janga, and J. Huppert, “Interfacing systems biology and synthetic biology,” Genome biol, vol. 10, iss. 6, pp. 309-309, 2009.
    author = {Lister, A and Charoensawan, V and De, S and James, K and Janga, S
    C and Huppert, J},
    title = {Interfacing systems biology and synthetic biology},
    journal = {Genome Biol},
    year = {2009},
    volume = {10},
    pages = {309-309},
    number = {6},
    abstract = {A report of BioSysBio 2009, the IET conference on Synthetic Biology,
    Systems Biology and Bioinformatics, Cambridge, UK, 23-25 March 2009.},
    doi = {10.1186/gb-2009-10-6-309},
    owner = {n8384838},
    pmid = {19591648},
    timestamp = {2013.05.09},
    url = {http://www.hubmed.org/display.cgi?uids=19591648}
  • [DOI] K. James, A. Wipat, and J. Hallinan, “Integration of full-coverage probabilistic functional networks with relevance to specific biological processes,” Data integration in the life sciences, pp. 31-46, 2009.
    author = {James, K and Wipat, A and Hallinan, J},
    title = {Integration of full-coverage probabilistic functional networks with
    relevance to specific biological processes},
    journal = {Data Integration in the Life Sciences},
    year = {2009},
    pages = {31--46},
    abstract = {Probabilistic functional integrated networks are powerful tools with
    which to draw inferences from high-throughput data. However, network
    analyses are generally not tailored to specific biological functions
    or processes. This problem may be overcome by extracting process-specific
    sub-networks, but this approach discards useful information and is
    of limited use in poorly annotated areas of the network. Here we
    describe an extension to existing integration methods which exploits
    dataset biases in order to emphasise interactions relevant to specific
    processes, without loss of data. We apply the method to high-throughput
    data for the yeast Saccharomyces cerevisiae, using Gene Ontology
    annotations for ageing and telomere maintenance as test processes.
    The resulting networks perform significantly better than unbiased
    networks for assigning function to unknown genes, and for clustering
    to identify important sets of interactions. We conclude that this
    integration method can be used to enhance network analysis with respect
    to specific processes of biological interest.},
    citeulike-article-id = {6129326},
    citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-642-02879-3_4},
    citeulike-linkout-1 = {http://www.springerlink.com/content/9mm86h61x56m866r},
    doi = {10.1007/978-3-642-02879-3_4},
    keywords = {biological\_processes, coverage\_analysis, data\_integration, dataset\_bias,
    owner = {n8384838},
    posted-at = {2009-11-17 11:09:24},
    priority = {2},
    timestamp = {2009.12.11},
    url = {http://dx.doi.org/10.1007/978-3-642-02879-3_4}
  • [DOI] A. Greenall, G. Lei, D. C. Swan, K. James, L. Wang, H. Peters, A. Wipat, D. J. Wilkinson, and D. Lydall, “A genome wide analysis of the response to uncapped telomeres in budding yeast reveals a novel role for the nad+ biosynthetic gene bna2 in chromosome end protection,” Genome biol, vol. 9, iss. 10, 2008.
    author = {Greenall, A and Lei, G and Swan, D C and James, K and Wang, L and
    Peters, H and Wipat, A and Wilkinson, D J and Lydall, D},
    title = {A genome wide analysis of the response to uncapped telomeres in budding
    yeast reveals a novel role for the NAD+ biosynthetic gene BNA2 in
    chromosome end protection},
    journal = {Genome Biol},
    year = {2008},
    volume = {9},
    number = {10},
    abstract = {Telomeres prevent the ends of eukaryotic chromosomes from being recognized
    as damaged DNA and protect against cancer and ageing. When telomere
    structure is perturbed, a co-ordinated series of events promote arrest
    of the cell cycle so that cells carrying damaged telomeres do not
    divide. In order to better understand the eukaryotic response to
    telomere damage, budding yeast strains harboring a temperature sensitive
    allele of an essential telomere capping gene (cdc13-1) were subjected
    to a transcriptomic study.The genome-wide response to uncapped telomeres
    in yeast cdc13-1 strains, which have telomere capping defects at
    temperatures above approximately 27 degrees C, was determined. Telomere
    uncapping in cdc13-1 strains is associated with the differential
    expression of over 600 transcripts. Transcripts affecting responses
    to DNA damage and diverse environmental stresses were statistically
    over-represented. BNA2, required for the biosynthesis of NAD+, is
    highly and significantly up-regulated upon telomere uncapping in
    cdc13-1 strains. We find that deletion of BNA2 and NPT1, which is
    also involved in NAD+ synthesis, suppresses the temperature sensitivity
    of cdc13-1 strains, indicating that NAD+ metabolism may be linked
    to telomere end protection.Our data support the hypothesis that the
    response to telomere uncapping is related to, but distinct from,
    the response to non-telomeric double-strand breaks. The induction
    of environmental stress responses may be a conserved feature of the
    eukaryotic response to telomere damage. BNA2, which is involved in
    NAD+ synthesis, plays previously unidentified roles in the cellular
    response to telomere uncapping.},
    doi = {10.1186/gb-2008-9-10-r146},
    owner = {n8384838},
    pmid = {18828915},
    timestamp = {2013.05.09},
    url = {http://www.hubmed.org/display.cgi?uids=18828915}
  • [DOI] S. G. Addinall, M. Downey, M. Yu, M. K. Zubko, J. Dewar, A. Leake, J. Hallinan, O. Shaw, K. James, D. J. Wilkinson, A. Wipat, D. Durocher, and D. Lydall, “A genomewide suppressor and enhancer analysis of cdc13-1 reveals varied cellular processes influencing telomere capping in saccharomyces cerevisiae,” Genetics, vol. 180, iss. 4, pp. 2251-2266, 2008.
    author = {Addinall, S G and Downey, M and Yu, M and Zubko, M K and Dewar, J
    and Leake, A and Hallinan, J and Shaw, O and James, K and Wilkinson,
    D J and Wipat, A and Durocher, D and Lydall, D},
    title = {A genomewide suppressor and enhancer analysis of cdc13-1 reveals
    varied cellular processes influencing telomere capping in Saccharomyces
    journal = {Genetics},
    year = {2008},
    volume = {180},
    pages = {2251-2266},
    number = {4},
    month = {Dec},
    abstract = {In Saccharomyces cerevisiae, Cdc13 binds telomeric DNA to recruit
    telomerase and to "cap" chromosome ends. In temperature-sensitive
    cdc13-1 mutants telomeric DNA is degraded and cell-cycle progression
    is inhibited. To identify novel proteins and pathways that cap telomeres,
    or that respond to uncapped telomeres, we combined cdc13-1 with the
    yeast gene deletion collection and used high-throughput spot-test
    assays to measure growth. We identified 369 gene deletions, in eight
    different phenotypic classes, that reproducibly demonstrated subtle
    genetic interactions with the cdc13-1 mutation. As expected, we identified
    DNA damage checkpoint, nonsense-mediated decay and telomerase components
    in our screen. However, we also identified genes affecting casein
    kinase II activity, cell polarity, mRNA degradation, mitochondrial
    function, phosphate transport, iron transport, protein degradation,
    and other functions. We also identified a number of genes of previously
    unknown function that we term RTC, for restriction of telomere capping,
    or MTC, for maintenance of telomere capping. It seems likely that
    many of the newly identified pathways/processes that affect growth
    of budding yeast cdc13-1 mutants will play evolutionarily conserved
    roles at telomeres. The high-throughput spot-testing approach that
    we describe is generally applicable and could aid in understanding
    other aspects of eukaryotic cell biology.},
    doi = {10.1534/genetics.108.092577},
    owner = {n8384838},
    pmid = {18845848},
    timestamp = {2013.05.09},
    url = {http://www.hubmed.org/display.cgi?uids=18845848}



Address: Room 918, School of Computing Science, Claremont Tower, Newcastle University, Newcastle upon Tyne, NE1 7RU

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