The Role of the Private Sector in Training the Next Generation of Biomedical Scientists

Summarizes the proceedings of a conference to address the unique contribution that private funders can make in ensuring that appropriate and adequate training programs are available for basic and clinical research. Offers conclusions and recommendations

Complex networks theory for analyzing metabolic networks

One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism, while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.Comment: 13 pages, 2 figure

Molecular Biology at the bedside: the impact of Genomics on the practice of medicine

Imagine being a newborn baby, discharged home after delivery, with a most unusual gift, a compact disc (CD) carrying all data on "My Genome". The parents would be most anxious to play it on their home PC. Soon, they could discover whether their child has been spared those major single gene disorders which uncle John had before he died young. The doctors had told them they could be selected out when they had opted for pre-gestational diagnosis and selective fertilisation.peer-reviewe

The Evolution of Cell Communication: The Road not Taken.

In the post-genomic era the complex problem of evolutionary biology can be tackled from the top-down, the bottom-up, or from the middle-out. Given the emergent and contingent nature of this process, we have chosen to take the latter approach, both as a mechanistic link to developmental biology and as a rational means of identifying signaling mechanisms based on their functional genomic significance. Using this approach, we have been able to configure a working model for lung evolution by reverse-engineering lung surfactant from the mammalian lung to the swim bladder of fish. Based on this archetypal cell-molecular model, we have reduced evolutionary biology to cell communication, starting with unicellular organisms communicating with the environment, followed by cell-cell communication to generate metazoa, culminating in the communication of genetic information between generations, i.e. reproduction. This model predicts the evolution of physiologic systems-including development, homeostasis, disease, regeneration/repair, and aging- as a logical consequence of biology reducing entropy. This approach provides a novel and robust way of formulating refutable, testable hypotheses to determine the ultimate origins and first principles of physiology, providing candidate genes for phenotypes hypothesized to have mediated evolutionary changes in structure and/or function. Ultimately, it will form the basis for predictive medicine and molecular bioethics, rather than merely showing associations between genes and pathology, which is an unequivocal Just So Story. In this new age of genomics, our reach must exceed our grasp

DRUG DISCOVERY: AN APPRAISAL

The process of drug discovery and development has undergone radical changes over the years. Introduction of several novel technologies in genomics, proteomics and other omics areas have enabled drug target identification and validation more specific. In silico virtual screening and other computational chemistry methods like QSAR (Quantitative Structure-Activity Relationship) and QSPR (Quantitative Structure-Property Relationship) have enabled the emergence of new drugs with minimal toxicity and higher efficacy in this post-genomics era. Moreover, initiative like Open Source Drug Discovery (OSDD) is playing a promising role in accelerating the pace of drug discovery process. Better understanding of these methods and initiatives by researchers will kindle interest towards adopting it. Hence, by this review, we intend to present a comprehensive view of overall transition and modernization of the drug discovery process and it's impacts on the scientific community.Â

Building Block and Building Rule: Dual Descriptor Method for Biological Sequence Analysis

The emergence of “Systems Biology” in recent years highlights the systematic viewpoint of bio-system modeling. Building on such a background, Dual Descriptor Method, a generic methodology for biological sequence analysis is proposed. From a systematic perspective, Dual Descriptor is defined as a two element set of Composition Weight Map and Position Weight Function which aim at reflecting the composition and permutation information of a sequence. An alternate training algorithm is provided to get an optimum description of the building patterns of the sequences. In this paper, dual descriptor method has been applied to the analysis of two typical problems of molecular biology: gene identification and the prediction of protein function. Satisfactory and insightful results are achieved. Owing to the generality of this methodology, dual descriptor method has wide application perspective for many problems of pattern recognition, especially those involved in “Systems Biology”