Biomedical subjects

John M Hancock

Publications and source records attributed to John M Hancock.

12 recordsLinked to original sources

PubMed2026

Open and sustainable AI: challenges, opportunities and the road ahead in the life sciences.

Artificial intelligence (AI) has seen transformative breakthroughs in the life sciences, expanding possibilities to interpret biological information at an unprecedented capacity. To maximize return on growing investments and accelerate progress, it is urgent to address long-standing research challenges arising from the rapid adoption of AI methods. We review the erosion of trust in AI outputs driven by poor reusability and reproducibility, and highlight their impact on environmental sustainability. Furthermore, we discuss the fragmented components of the AI ecosystem and lack of guiding pathways to support open and sustainable AI model development. In response, this Perspective introduces practical open and sustainable AI recommendations mapped to over 300 ecosystem components and provides guiding implementation pathways. Our work connects researchers with relevant AI resources, facilitating the implementation of sustainable, reusable and reproducible AI. Built upon community consensus and aligned to existing efforts, these outputs will aid future policy development and structured pathways for guiding AI implementation.

Artificial Intelligence↗

PubMed2006

Understanding mammalian genetic systems: the challenge of phenotyping in the mouse.

Understanding mammalian genetic systems is predicated on the determination of the relationship between genetic variation and phenotype. Several international programmes are under way to deliver mutations in every gene in the mouse genome. The challenge for mouse geneticists is to develop approaches that will provide comprehensive phenotype datasets for these mouse mutant libraries. Several factors are critical to success in this endeavour. It will be important to catalogue assay and environment and where possible to adopt standardised procedures for phenotyping tests along with common environmental conditions to ensure comparable datasets of phenotypes. Moreover, the scale of the task underlines the need to invest in technological development improving both the speed and cost of phenotyping platforms. In addition, it will be necessary to develop new informatics standards that capture the phenotype assay as well as other factors, genetic and environmental, that impinge upon phenotype outcome.

Animals↗

PubMed2005

Gene factories, microfunctionalization and the evolution of gene families.

Gene duplication has long been considered an important force in genome evolution. In this article, I consider families of tandemly duplicated genes that show 'microfunctionalization' - genes encoding similar proteins with subtly different functions, such as olfactory receptors. I discuss the genomic processes giving rise to such microfunctionalized gene families and suggest that, like sites of chromosomal rearrangement and breakage, they are associated with relatively high concentrations of repetitive elements. I suggest that microfunctionalized gene families arise within gene factories: genomic regions rich in repetitive elements that undergo increased levels of unequal crossing-over.

Animals↗

PubMed2005

EMPReSS: European mouse phenotyping resource for standardized screens.

UNLABELLED: Standardized phenotyping protocols are essential for the characterization of phenotypes so that results are comparable between different laboratories and phenotypic data can be related to ontological descriptions in an automated manner. We describe a web-based resource for the visualization, searching and downloading of standard operating procedures and other documents, the European Mouse Phenotyping Resource for Standardized Screens-EMPReSS. AVAILABILITY: Direct access: http://www.empress.har.mrc.ac.uk CONTACT: e.green@har.mrc.ac.uk.

Animals↗

PubMed2004

Using ontologies to describe mouse phenotypes.

The mouse is an important model of human genetic disease. Describing phenotypes of mutant mice in a standard, structured manner that will facilitate data mining is a major challenge for bioinformatics. Here we describe a novel, compositional approach to this problem which combines core ontologies from a variety of sources. This produces a framework with greater flexibility, power and economy than previous approaches. We discuss some of the issues this approach raises.

Animals↗

PubMed2004

Simple sequence repeats in proteins and their significance for network evolution.

Only 5-6% of mammalian genomes are genes; the remainders are made up primarily of transposable elements and different types of simple sequence repeat (SSRs) (micro- and minisatellites and cryptic repeats), which tend to accumulate in organisms with larger genomes. SSRs are also found at the level of protein sequences and may or may not be encoded by SSRs at the DNA sequence level. Studies of proteins containing SSRs indicate that they tend to belong to particular functional classes, particularly transcription factors and protein kinases. Protein SSRs coded for by pure codon repeats evolve rapidly while those encoded by mixtures of codons evolve slowly. We outline a conceptualization of how protein SSRs may arise and become fixed in proteins during evolution, and suggest that emergence and change in length of protein SSRs may affect the topology of protein interaction networks.

Amino Acid Sequence↗

PubMed2004

CRAVE: a database, middleware and visualization system for phenotype ontologies.

MOTIVATION: A major challenge in modern biology is to link genome sequence information to organismal function. In many organisms this is being done by characterizing phenotypes resulting from mutations. Efficiently expressing phenotypic information requires combinatorial use of ontologies. However tools are not currently available to visualize combinations of ontologies. Here we describe CRAVE (Concept Relation Assay Value Explorer), a package allowing storage, active updating and visualization of multiple ontologies. RESULTS: CRAVE is a web-accessible JAVA application that accesses an underlying MySQL database of ontologies via a JAVA persistent middleware layer (Chameleon). This maps the database tables into discrete JAVA classes and creates memory resident, interlinked objects corresponding to the ontology data. These JAVA objects are accessed via calls through the middleware's application programming interface. CRAVE allows simultaneous display and linking of multiple ontologies and searching using Boolean and advanced searches.

Algorithms↗

PubMed2004

Organization and evolution of a gene-rich region of the mouse genome: a 12.7-Mb region deleted in the Del(13)Svea36H mouse.

Del(13)Svea36H (Del36H) is a deletion of approximately 20% of mouse chromosome 13 showing conserved synteny with human chromosome 6p22.1-6p22.3/6p25. The human region is lost in some deletion syndromes and is the site of several disease loci. Heterozygous Del36H mice show numerous phenotypes and may model aspects of human genetic disease. We describe 12.7 Mb of finished, annotated sequence from Del36H. Del36H has a higher gene density than the draft mouse genome, reflecting high local densities of three gene families (vomeronasal receptors, serpins, and prolactins) which are greatly expanded relative to human. Transposable elements are concentrated near these gene families. We therefore suggest that their neighborhoods are gene factories, regions of frequent recombination in which gene duplication is more frequent. The gene families show different proportions of pseudogenes, likely reflecting different strengths of purifying selection and/or gene conversion. They are also associated with relatively low simple sequence concentrations, which vary across the region with a periodicity of approximately 5 Mb. Del36H contains numerous evolutionarily conserved regions (ECRs). Many lie in noncoding regions, are detectable in species as distant as Ciona intestinalis, and therefore are candidate regulatory sequences. This analysis will facilitate functional genomic analysis of Del36H and provides insights into mouse genome evolution.

Animals↗

PubMed2004

A bigger mouse? The rat genome unveiled.

Rattus norvegicus is an important experimental organism and interesting to evolutionary biologists. The recently published draft rat genome sequence provides us with insights into both the rat's evolution and its physiology. We learn more about genome evolution and, in particular, the adaptive significance of gene family expansions and the evolution of rodent genomes, which appears to have decelerated since the divergence of mouse and rat. An important observation is that some regions of genomes, many in noncoding regions, show very high sequence conservation, while others show unexpectedly fast evolution. Both of these may be pointers to functional significance.

Animals↗

PubMed2003

PlantProm: a database of plant promoter sequences.

PlantProm DB, a plant promoter database, is an annotated, non-redundant collection of proximal promoter sequences for RNA polymerase II with experimentally determined transcription start site(s), TSS, from various plant species. The first release (2002.01) of PlantProm DB contains 305 entries including 71, 220 and 14 promoters from monocot, dicot and other plants, respectively. It provides DNA sequence of the promoter regions (-200 : +51) with TSS on the fixed position +201, taxonomic/promoter type classification of promoters and Nucleotide Frequency Matrices (NFM) for promoter elements: TATA-box, CCAAT-box and TSS-motif (Inr). Analysis of TSS-motifs revealed that their composition is different in dicots and monocots, as well as for TATA and TATA-less promoters. The database serves as learning set in developing plant promoter prediction programs. One such program (TSSP) based on discriminant analysis has been created by Softberry Inc. and the application of a support ftp: vector machine approach for promoter identification is under development. PlantProm DB is available at http://mendel.cs.rhul.ac.uk/ and http://www.softberry.com/.

Databases, Nucleic Acid↗

PubMed2002

Genome size and the accumulation of simple sequence repeats: implications of new data from genome sequencing projects.

The relationship between the level of repetitiveness in genomic sequences and genome size has been re-investigated making use of the rapidly growing database of complete eubacterial and archaeal genome sequences combined with the fragmentary but now large amount of data from eukaryotic genomes. Relative simplicity factors (RSFs), which measure the repetitiveness of sequences, were calculated and significantly simple motifs (SSMs), which identify the kinds of sequences that are repeated, were identified. A previously reported correlation between genome size and repetitiveness was confirmed, but it was shown that the higher RSFs seen in eukaryotic genomes also reflect a generally higher level of repetitiveness independent of genome size differences. Differences in genome size are responsible for about 10% of the variance in RSF seen between species. The spectrum of SSMs seen within a genome differed markedly within the eubacteria but less so in eukaryotes and, particularly, in archaea. Species with SSM spectra that differ from the norm tend also to have high RSFs for their genome size and to be pathogens that make use of repetitive sequences to avoid host defence responses. Some of the variance in repetitiveness seen in other species may therefore also reflect the action of selection, although other forces such as variation in the effectiveness of mechanisms for regulating slippage errors of replication, may also be important.

Animals↗

PubMed2002

Detecting cryptically simple protein sequences using the SIMPLE algorithm.

MOTIVATION: Low-complexity or cryptically simple sequences are widespread in protein sequences but their evolution and function are poorly understood. To date methods for the detection of low complexity in proteins have been directed towards the filtering of such regions prior to sequence homology searches but not to the analysis of the regions per se. However, many of these regions are encoded by non-repetitive DNA sequences and may therefore result from selection acting on protein structure and/or function. RESULTS: We have developed a new tool, based on the SIMPLE algorithm, that facilitates the quantification of the amount of simple sequence in proteins and determines the type of short motifs that show clustering above a certain threshold. By modifying the sensitivity of the program simple sequence content can be studied at various levels, from highly organised tandem structures to complex combinations of repeats. We compare the relative amount of simplicity in different functional groups of yeast proteins and determine the level of clustering of the different amino acids in these proteins. AVAILABILITY: The program is available on request or online at http://www.biochem.ucl.ac.uk/bsm/SIMPLE.

Algorithms↗