Modular Biological Function Is Most Effectively Captured by Combining Molecular Interaction Data Types

PublishedLarge-scale molecular interaction data sets have the potential to provide a comprehensive, system-wide understanding of biological function. Although individual molecules can be promiscuous in terms of their contribution to function, molecular functions emerge from the specific interactions of molecules giving rise to modular organisation. As functions often derive from a range of mechanisms, we demonstrate that they are best studied using networks derived from different sources. Implementing a graph partitioning algorithm we identify subnetworks in yeast protein-protein interaction (PPI), genetic interaction and gene co-regulation networks. Among these subnetworks we identify cohesive subgraphs that we expect to represent functional modules in the different data types. We demonstrate significant overlap between the subgraphs generated from the different data types and show these overlaps can represent related functions as represented by the Gene Ontology (GO). Next, we investigate the correspondence between our subgraphs and the Gene Ontology. This revealed varying degrees of coverage of the biological process, molecular function and cellular component ontologies, dependent on the data type. For example, subgraphs from the PPI show enrichment for 84%, 58% and 93% of annotated GO terms, respectively. Integrating the interaction data into a combined network increases the coverage of GO. Furthermore, the different annotation types of GO are not predominantly associated with one of the interaction data types. Collectively our results demonstrate that successful capture of functional relationships by network data depends on both the specific biological function being characterised and the type of network data being used. We identify functions that require integrated information to be accurately represented, demonstrating the limitations of individual data types. Combining interaction subnetworks across data types is therefore essential for fully understanding the complex and emergent nature of biological function.JIM was funded by a Biotechnology and Biological Sciences Research Council (BBSRC) CASE studentship with industry partner Pfizer and RMA by a BBSRC studentship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Cancer's sweet tooth for serine

Exemplified by the cancer cell's preference for glycolysis (the Warburg effect), altered metabolism has taken centerstage as an emerging hallmark of cancer. Charting the landscape of cancer metabolic addictions should reveal new avenues for therapeutic attack. Two recent studies found subsets of human melanoma and breast cancers to have high levels of phosphoglycerate dehydrogenase (PHGDH), a key enzyme for serine biosynthesis, and these cancer cells are dependent on PHGDH for their growth and survival. Tumors may thus harbor distinct metabolic alterations to support their malignancy, and targeting enzymes such as PHGDH might prove a viable therapeutic strategy in this scenario

Assessing computer skills in Tanzanian medical students: an elective experience

Background: One estimate suggests that by 2010 more than 30% of a physician's time will be spent using information technology tools. The aim of this study is to assess the information and communication technologies (ICT) skills of medical students in Tanzania. We also report a pilot intervention of peer mentoring training in ICT by medical students from the UK tutoring students in Tanzania. Methods: Design: Cross sectional study and pilot intervention study. Participants: Fourth year medical students (n = 92) attending Muhimbili University College of Health Sciences, Dar es Salaam, Tanzania. Main outcome measures: Self-reported assessment of competence on ICT-related topics and ability to perform specific ICT tasks. Further information related to frequency of computer use (hours per week), years of computer use, reasons for use and access to computers. Skills at specific tasks were reassessed for 12 students following 4 to 6 hours of peer mentoring training. Results: The highest levels of competence in generic ICT areas were for email, Internet and file management. For other skills such as word processing most respondents reported low levels of competence. The abilities to perform specific ICT skills were low – less than 60% of the participants were able to perform the core specific skills assessed. A period of approximately 5 hours of peer mentoring training produced an approximate doubling of competence scores for these skills. Conclusion: Our study has found a low level of ability to use ICT facilities among medical students in a leading university in sub-Saharan Africa. A pilot scheme utilising UK elective students to tutor basic skills showed potential. Attention is required to develop interventions that can improve ICT skills, as well as computer access, in order to bridge the digital divide

Measuring portfolio performance using a modified measure of risk

This paper reports the results of an investigation into the properties of a theoretical modification of beta proposed by Leland (1999) and based on earlier work of Rubinstein (1976). It is shown that when returns are elliptically symmetric, beta is the appropriate measure of risk and that there are other situations in which the modified beta will be similar to the traditional measure based on the capital asset pricing model. For the case where returns have a normal distribution, it is shown that the criterion either does not exist or reduces exactly to the conventional beta. It is therefore conjectured that the modified measure will only be useful for portfolios that have nonstandard return distributions which incorporate skewness. For such situations, it is shown how to estimate the measure using regression and how to compare the resulting statistic with a traditional estimated beta using Hotelling's test. An empirical study based on stocks from the FTSE350 does not find evidence to support the use of the new measure even in the presence of skewness.Journal of Asset Management (2007) 7, 388-403. doi:10.1057/palgrave.jam.225005

Optimal search strategies for identifying sound clinical prediction studies in EMBASE

BACKGROUND: Clinical prediction guides assist clinicians by pointing to specific elements of the patient's clinical presentation that should be considered when forming a diagnosis, prognosis or judgment regarding treatment outcome. The numbers of validated clinical prediction guides are growing in the medical literature, but their retrieval from large biomedical databases remains problematic and this presents a barrier to their uptake in medical practice. We undertook the systematic development of search strategies ("hedges") for retrieval of empirically tested clinical prediction guides from EMBASE. METHODS: An analytic survey was conducted, testing the retrieval performance of search strategies run in EMBASE against the gold standard of hand searching, using a sample of all 27,769 articles identified in 55 journals for the 2000 publishing year. All articles were categorized as original studies, review articles, general papers, or case reports. The original and review articles were then tagged as 'pass' or 'fail' for methodologic rigor in the areas of clinical prediction guides and other clinical topics. Search terms that depicted clinical prediction guides were selected from a pool of index terms and text words gathered in house and through request to clinicians, librarians and professional searchers. A total of 36,232 search strategies composed of single and multiple term phrases were trialed for retrieval of clinical prediction studies. The sensitivity, specificity, precision, and accuracy of search strategies were calculated to identify which were the best. RESULTS: 163 clinical prediction studies were identified, of which 69 (42.3%) passed criteria for scientific merit. A 3-term strategy optimized sensitivity at 91.3% and specificity at 90.2%. Higher sensitivity (97.1%) was reached with a different 3-term strategy, but with a 16% drop in specificity. The best measure of specificity (98.8%) was found in a 2-term strategy, but with a considerable fall in sensitivity to 60.9%. All single term strategies performed less well than 2- and 3-term strategies. CONCLUSION: The retrieval of sound clinical prediction studies from EMBASE is supported by several search strategies

Dendritic Spine Shape Analysis: A Clustering Perspective

Functional properties of neurons are strongly coupled with their morphology. Changes in neuronal activity alter morphological characteristics of dendritic spines. First step towards understanding the structure-function relationship is to group spines into main spine classes reported in the literature. Shape analysis of dendritic spines can help neuroscientists understand the underlying relationships. Due to unavailability of reliable automated tools, this analysis is currently performed manually which is a time-intensive and subjective task. Several studies on spine shape classification have been reported in the literature, however, there is an on-going debate on whether distinct spine shape classes exist or whether spines should be modeled through a continuum of shape variations. Another challenge is the subjectivity and bias that is introduced due to the supervised nature of classification approaches. In this paper, we aim to address these issues by presenting a clustering perspective. In this context, clustering may serve both confirmation of known patterns and discovery of new ones. We perform cluster analysis on two-photon microscopic images of spines using morphological, shape, and appearance based features and gain insights into the spine shape analysis problem. We use histogram of oriented gradients (HOG), disjunctive normal shape models (DNSM), morphological features, and intensity profile based features for cluster analysis. We use x-means to perform cluster analysis that selects the number of clusters automatically using the Bayesian information criterion (BIC). For all features, this analysis produces 4 clusters and we observe the formation of at least one cluster consisting of spines which are difficult to be assigned to a known class. This observation supports the argument of intermediate shape types.Comment: Accepted for BioImageComputing workshop at ECCV 201

The intriguing evolutionary dynamics of plant mitochondrial DNA

The mitochondrial genome of plants is-in every respect and for yet unclear reasons-very different from the well-studied one of animals. Thanks to next-generation sequencing technologies, Davila et al. precisely characterized the role played by recombination and DNA repair in controlling mitochondrial variations in Arabidopsis thaliana, thus opening new perspectives on the long-term evolution of this intriguing genome

Al8Mn5 in High-Pressure Die Cast AZ91: Twinning, Morphology and Size Distributions

EPSRC (UK); National Natural Science Foundation of China

Long-distance quantum communication with atomic ensembles and linear optics

Quantum communication holds a promise for absolutely secure transmission of secret messages and faithful transfer of unknown quantum states. Photonic channels appear to be very attractive for physical implementation of quantum communication. However, due to losses and decoherence in the channel, the communication fidelity decreases exponentially with the channel length. We describe a scheme that allows to implement robust quantum communication over long lossy channels. The scheme involves laser manipulation of atomic ensembles, beam splitters, and single-photon detectors with moderate efficiencies, and therefore well fits the status of the current experimental technology. We show that the communication efficiency scale polynomially with the channel length thereby facilitating scalability to very long distances.Comment: 2 tex files (Main text + Supplement), 4 figure

Fabrication and operation of a two-dimensional ion-trap lattice on a high-voltage microchip

Microfabricated ion traps are a major advancement towards scalable quantum computing with trapped ions. The development of more versatile ion-trap designs, in which tailored arrays of ions are positioned in two dimensions above a microfabricated surface, will lead to applications in fields as varied as quantum simulation, metrology and atom–ion interactions. Current surface ion traps often have low trap depths and high heating rates, because of the size of the voltages that can be applied to them, limiting the fidelity of quantum gates. Here we report on a fabrication process that allows for the application of very high voltages to microfabricated devices in general and use this advance to fabricate a two-dimensional ion-trap lattice on a microchip. Our microfabricated architecture allows for reliable trapping of two-dimensional ion lattices, long ion lifetimes, rudimentary shuttling between lattice sites and the ability to deterministically introduce defects into the ion lattice