10,360 research outputs found
Natural Variation and Neuromechanical Systems
Natural variation plays an important but subtle and often ignored role in neuromechanical systems. This is especially important when designing for living or hybrid systems \ud
which involve a biological or self-assembling component. Accounting for natural variation can be accomplished by taking a population phenomics approach to modeling and analyzing such systems. I will advocate the position that noise in neuromechanical systems is partially represented by natural variation inherent in user physiology. Furthermore, this noise can be augmentative in systems that couple physiological systems with technology. There are several tools and approaches that can be borrowed from computational biology to characterize the populations of users as they interact with the technology. In addition to transplanted approaches, the potential of natural variation can be understood as having a range of effects on both the individual's physiology and function of the living/hybrid system over time. Finally, accounting for natural variation can be put to good use in human-machine system design, as three prescriptions for exploiting variation in design are proposed
Systems Biology and the Development of Vaccines and Drugs for Malaria Treatments
The sequencing race has ended and the functional race has already begun. Microarray technology enables
simultaneous gene expression analysis of thousands of genes, enabling a snapshot of an organisms’
transcriptome at an unprecedented resolution. The close correlation between gene transcription and
function, allow the inference of biological processes from the assessed transcriptome profile. Among the
sophisticated analytical problems in microarray technology at the front and back ends respectively, are the
selection of optimal DNA oligos and computational analysis of the genes expression. In this review paper,
we analyse important methods in use today in customized oligos design. In the course of executing this,
we discovered that the oligos designer algorithm hanged on gene PFA0135w of chromosome 1, while
designing oligos for the gene sequences of Plasmodium falciparum. We do not know the reason for this
yet, as the algorithm runs on other sequences like the yeast (Saccharomyces cervisiae) and Neurospora
crassa. We conclude the paper highlighting the procedures encompassing the back end phase and discuss
their application to the development of vaccines and drugs for malaria treatment. Note that, malaria is the
cause of significant global morbidity and mortality with 300-500 million cases annually. Our aims are not
ends, but a means to achieve the following: Iterate the need for experimental biologists to (i) know how to
design their customized oligos and (ii) have some idea about gene expression analysis and the need for
cooperation between experimental biologists and their counterpart, the computational biologists. These
will help experimental biologists to coordinate very well the front and the back ends of the system
biology analysis of the whole genome effectively
Theories, models, simulations: a computational challenge
In this talk I would like to illustrate with examples taken from Quantum
Field Theory and Biophysics how an intelligent exploitation of the
unprecedented power of today's computers could led not only to the solution of
pivotal problems in the theory of Strong Interactions, but also to the
emergence of new lines of interdisciplinary research, while at the same time
pushing the limits of modeling to the realm of living systems.Comment: 19 pages, 1 figure, conference pape
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