Frontiers in the Convergence of Bioscience and Information Technology
Identifieur interne : 000D06 ( Pmc/Curation ); précédent : 000D05; suivant : 000D07Frontiers in the Convergence of Bioscience and Information Technology
Auteurs : Daniel Howard [Royaume-Uni]Source :
- Journal of Biomedicine and Biotechnology [ 1110-7243 ] ; 2008.
Url:
DOI: 10.1155/2008/728908
PubMed: 18769494
PubMed Central: 2519141
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Frontiers in the Convergence of Bioscience and Information Technology</title>
<author><name sortKey="Howard, Daniel" sort="Howard, Daniel" uniqKey="Howard D" first="Daniel" last="Howard">Daniel Howard</name>
<affiliation wicri:level="1"><nlm:aff id="I1">QinetiQ Limited, Malvern Technology Centre, St Andrew's Road, Malvern, Worcestershire WR14 3PS, UK</nlm:aff>
<country xml:lang="fr">Royaume-Uni</country>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Frontiers in the Convergence of Bioscience and Information Technology</title>
<author><name sortKey="Howard, Daniel" sort="Howard, Daniel" uniqKey="Howard D" first="Daniel" last="Howard">Daniel Howard</name>
<affiliation wicri:level="1"><nlm:aff id="I1">QinetiQ Limited, Malvern Technology Centre, St Andrew's Road, Malvern, Worcestershire WR14 3PS, UK</nlm:aff>
<country xml:lang="fr">Royaume-Uni</country>
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<series><title level="j">Journal of Biomedicine and Biotechnology</title>
<idno type="ISSN">1110-7243</idno>
<idno type="eISSN">1110-7251</idno>
<imprint><date when="2008">2008</date>
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<front><journal-meta><journal-id journal-id-type="nlm-ta">J Biomed Biotechnol</journal-id>
<journal-id journal-id-type="publisher-id">JBB</journal-id>
<journal-title>Journal of Biomedicine and Biotechnology</journal-title>
<issn pub-type="ppub">1110-7243</issn>
<issn pub-type="epub">1110-7251</issn>
<publisher><publisher-name>Hindawi Publishing Corporation</publisher-name>
</publisher>
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<article-meta><article-id pub-id-type="pmid">18769494</article-id>
<article-id pub-id-type="pmc">2519141</article-id>
<article-id pub-id-type="doi">10.1155/2008/728908</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Editorial</subject>
</subj-group>
</article-categories>
<title-group><article-title>Frontiers in the Convergence of Bioscience and Information Technology</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Howard</surname>
<given-names>Daniel</given-names>
</name>
<xref ref-type="aff" rid="I1"></xref>
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<aff id="I1">QinetiQ Limited, Malvern Technology Centre, St Andrew's Road, Malvern, Worcestershire WR14 3PS, UK</aff>
<author-notes><corresp id="cor1">*Daniel Howard: <email>dr.daniel.howard@gmail.com</email>
</corresp>
</author-notes>
<pub-date pub-type="ppub"><year>2008</year>
</pub-date>
<pub-date pub-type="epub"><day>24</day>
<month>8</month>
<year>2008</year>
</pub-date>
<volume>2008</volume>
<elocation-id>728908</elocation-id>
<history><date date-type="received"><day>15</day>
<month>6</month>
<year>2008</year>
</date>
<date date-type="accepted"><day>15</day>
<month>6</month>
<year>2008</year>
</date>
</history>
<permissions><copyright-statement>Copyright © 2008 Daniel Howard.</copyright-statement>
<copyright-year>2008</copyright-year>
<license license-type="open-access"><p>This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
</license>
</permissions>
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</front>
<body><p>This special issue places
its emphasis on the crossroads between computational modeling and the
biosciences. It is ambitious but fruitful interdisciplinary research, and this
special issue aims to illustrate different presentations of it. It offers those
advancing knowledge in some particular area the view to related research
activity and opportunities.</p>
<p>Many of the articles exemplify how mathematics and
computer simulation inform experimentation to obtain new knowledge about
nature. Some articles represent discoveries and others review, introduce, test,
or trial algorithms or tools that are potentially helpful to arrive at
discoveries. A few articles, however, are reversed in that they demonstrate how
bioinspired algorithms or biological devices can solve hard computational
challenges. Consider that manipulating chemicals may compute an answer much faster
than by means of the standard silicon-based computer and within this special issue there is an article by K. Li et al. describing the principles by which such a DNA computer can compromise an encryption algorithm that is central to present day secure communications.</p>
<p>One might classify the articles in this special issue into
three groupings: (1) those concerned with biological problems from molecular cell biology to systems biology, (2)
those which apply classification algorithms in cancer diagnosis and methods of computer vision to
anatomy, and finally (3) those
which offer new knowledge or possibilities in bioengineering and
biomedicine.</p>
<p>The first grouping covers Systems Biology, an exciting interdisciplinary field
that marries experiments with computer simulations. Synthetic and systems
biotechnology, for example, is a technology at these frontiers that aims to sequester the services of micro-organisms for the
benefit of mankind. Its ability to produce foods in a vat that would otherwise
take up valuable land resources with conventional agriculture will offer
flexibility in food production. In their article, M.-J. Han et al. reveal how
knowledge and understanding of cell physiology in the presence of oleic
acid are obtained for <italic>E. coli</italic>
. Interesting research about signaling
networks in retina, as induced by light exposure in mice, is presented by J.
Krishnan et al. showing marked alterations in gene expression upon light exposure.
Certain transcription factors are discovered to be important for the responses
to light-induced retinal loss, revealing that many of the apoptosis-related
genes are up- or downregulated in this process. In their article, R.
Moreno-Sanchez et al. offer a very useful review of metabolic control analysis
(MCA), a tool that represents a type of engineering control theory for cell
biology and when applicable MCA can help to grapple with an understanding of
the complex control of the metabolic pathways.</p>
<p>Also in the first grouping, three articles by S. Huang and his colleagues develop the emergent and interdisciplinary field of infectomics, which is
the study of infectomes encoded by the genomes of microbes and their hosts.
Infectomics has potential to advance the rational strategies that will prevent
and treat infectious diseases as these could require a full appreciation of the
infectomes that contribute to microbial infections. There is a need to figure
out how to dissect the dynamic duality relationship between symbiosis and
pathogenesis in microbial infections, and advocates of this new field oppose what they see as
the misguided, though current and popular,
reductionist and Manichean views of the microbe-human host relationship.
Another article on the topic of infectious diseases by K.-Y. Hwa et al.
investigates the emerging and life-threatening infectious disease known as
SARS, where there is a compelling need for the development of effective
therapeutics. Their article presents interesting and potentially important
findings, that molecular mimicry occurs between SARS-CoV and host proteins.
They investigate how to predict those peptides that are worthy of exploration
for their biological activity. The article by L. Hamel et al. provides novel insight into the field of phylogenetics with the idea of the spectra of a tree, and reviewers identified its potential to compare with phylogenetic trees across different genes and for detecting lateral gene transfer.</p>
<p>The first grouping of articles also covers specialist numerical
algorithms for gene sequencing, genomics, and proteomics. With genomic
sequencing, an error in contig assembly causes serious error proliferation, and
ConPath (P.-G. Kim et al.) is a tool that can address this problem. It
constructs scaffolds, ordering and orienting separate sequence contigs by exploiting
the mate-pair information between contig pairs. C.-K. Chan et al. develop the
growing self-organized map (GSOM) for binning (the clustering of these
unassembled DNA sequences). They report improvements over the binning that
combines oligonucleotide frequency and self-organizing maps (SOMs), and
identify suitable training features and quantitative measures for assessing
results in this area. In their article, K. Han et al. develop an algorithm to
search for the highly connected subgraphs in protein interaction networks
because this might be helpful to predict protein function. The article by
Mi-Young Kim expounds a new approach to the very important problem of text
mining of biomolecular text, and is specifically concerned with detecting gene
interactions. There follow two articles in biological chemistry with computational
chemistry. C.-J. Kuo et al. solve the crystal structure of H. pylori undecaprenyl pyrophosphate synthase and perform virtual screening of inhibitors from a chemical library of thousands of compounds. M. Muddassar et al. explore receptor-guided 3D-QSAR to design
IGF-1R inhibitors by pursuing careful statistical analysis to interpret the
models that are obtained with the help of contour maps. The article by J.-C.
Lue and W.-C. Fang proposes a compact integrated microsystem solution for
robust, real-time, and onsite genetic analysis. It uses a preceding VLSI
differential logarithm microchip that is designed to compute the logarithm of
the normalized input fluorescence signals and a succeeding VLSI artificial
neural network (ANN) processor chip to analyze the processed signals from the
differential logarithm stage. It is submitted that the version of ANN chosen is
particularly adept at recognizing the low-fluorescence patterns.</p>
<p>The second grouping includes cancer diagnosis, biomedical imaging and also computational anatomy (the study of anatomical variability in health and disease via deformable templates as inspired by D'Arcy Wentworth Thompson). These fields sit in the frontiers of biosciences, image analysis,
mathematics, and numerical methods. In this grouping, a number of articles
implement (D. Howard et al.), evaluate (N. A. Lee et al.), or introduce (J. Kolibal et al.) techniques of image analysis to cluster, segment, or
analyze images, or extract information or enrich biomedical images. For
example, J. Woo et al. discuss multimodal data integration for computer-aided
ablation of atrial fibrillation. Y. Park et al. analyze the interpoint
dissimilarity comparisons in the hippocampus shape space to distinguish between
hippocampi of subjects with three conditions (clinically depressed, high risk,
and control subject), and discover the high-risk population closer in shape
space to the control population than to the clinically depressed population.
Additionally, they find that the left hippocampi carry more information than do
the right. In their article, N. A. Lee et al. examine performance in the
segmentation of high-resolution MRI subvolumes containing hippocampus,
prefrontal cortex, and occipital lobe, as acquired on different scanners. They
offer evidence that the alternating kernel mixture algorithm outperforms
alternatives on the ten datasets considered. The availability of powerful
imaging and other sensors, the availability of information technology, and the
nature of modern threats point to population biometrics as a topic of enormous
current and future importance. Implementing biometrics well is hard and is not
yet properly understood. The methodological paper by Y. N. Shin et al. proposes
a formal performance evaluation model for a biometric recognition system. They
also implement face recognition systems based on the proposed model. The model
seems to be useful in terms of database availability, compliance with
standards, and evaluation costs. The proposed formalism may gain traction for
other biometrics, and it has the potential to inform strategies for
population-based biomedical imaging performance evaluation and standardization. The last article of this second grouping by J. Wichard et al.
evaluates how bioinspired and computational intelligence algorithms compare in providing reliable early cancer diagnosis.</p>
<p>The third grouping comprises articles which cover
advances in biomechanics, biophysics, and biomedicine. It includes a detailed
biomechanics study by J. S. Merritt et al. on the equine distal forelimb, which
is a common location of injuries related to mechanical overload. These authors
combine analysis with experiment in a fairly thorough but concise way to
calculate the forces in the major tendons and joint reaction from kinematic and
kinetic data of walking and trotting horses. Their findings point to the
importance of muscle tendon wrapping when evaluating joint loading in the distal
forelimb. The article by C. Handapangoda and M. Premaratne describes a novel
numerical technique for modeling optical pulse propagation in inhomogeneous
scattering and absorption cross-sections through weakly scattering biological
tissues. The design of implantable electronic devices to interact with
the nervous system is an active field, the development of an efficient system
for long-term stimulation of the optic nerve is rather timely (e.g., it is
required to evaluate the long-term safety of retinal implants), and the
methodological report by J. A. Zhou et al. describes the design of a
suprachoroidal electrical retinal stimulator for long-term application. Finally, two articles in the third category advance novel robots (H. Sawada et al.) and haptic
solutions (K.-U. Kyung et al.) that interact with the human senses and which might prove helpful to the sensorially impaired.</p>
<p><named-content content-type="signature">Daniel Howard</named-content>
</p>
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