32,438 research outputs found
Towards Understanding the Origin of Genetic Languages
Molecular biology is a nanotechnology that works--it has worked for billions
of years and in an amazing variety of circumstances. At its core is a system
for acquiring, processing and communicating information that is universal, from
viruses and bacteria to human beings. Advances in genetics and experience in
designing computers have taken us to a stage where we can understand the
optimisation principles at the root of this system, from the availability of
basic building blocks to the execution of tasks. The languages of DNA and
proteins are argued to be the optimal solutions to the information processing
tasks they carry out. The analysis also suggests simpler predecessors to these
languages, and provides fascinating clues about their origin. Obviously, a
comprehensive unraveling of the puzzle of life would have a lot to say about
what we may design or convert ourselves into.Comment: (v1) 33 pages, contributed chapter to "Quantum Aspects of Life",
edited by D. Abbott, P. Davies and A. Pati, (v2) published version with some
editin
An Introduction to Programming for Bioscientists: A Python-based Primer
Computing has revolutionized the biological sciences over the past several
decades, such that virtually all contemporary research in the biosciences
utilizes computer programs. The computational advances have come on many
fronts, spurred by fundamental developments in hardware, software, and
algorithms. These advances have influenced, and even engendered, a phenomenal
array of bioscience fields, including molecular evolution and bioinformatics;
genome-, proteome-, transcriptome- and metabolome-wide experimental studies;
structural genomics; and atomistic simulations of cellular-scale molecular
assemblies as large as ribosomes and intact viruses. In short, much of
post-genomic biology is increasingly becoming a form of computational biology.
The ability to design and write computer programs is among the most
indispensable skills that a modern researcher can cultivate. Python has become
a popular programming language in the biosciences, largely because (i) its
straightforward semantics and clean syntax make it a readily accessible first
language; (ii) it is expressive and well-suited to object-oriented programming,
as well as other modern paradigms; and (iii) the many available libraries and
third-party toolkits extend the functionality of the core language into
virtually every biological domain (sequence and structure analyses,
phylogenomics, workflow management systems, etc.). This primer offers a basic
introduction to coding, via Python, and it includes concrete examples and
exercises to illustrate the language's usage and capabilities; the main text
culminates with a final project in structural bioinformatics. A suite of
Supplemental Chapters is also provided. Starting with basic concepts, such as
that of a 'variable', the Chapters methodically advance the reader to the point
of writing a graphical user interface to compute the Hamming distance between
two DNA sequences.Comment: 65 pages total, including 45 pages text, 3 figures, 4 tables,
numerous exercises, and 19 pages of Supporting Information; currently in
press at PLOS Computational Biolog
A Process Calculus for Molecular Interaction Maps
We present the MIM calculus, a modeling formalism with a strong biological
basis, which provides biologically-meaningful operators for representing the
interaction capabilities of molecular species. The operators of the calculus
are inspired by the reaction symbols used in Molecular Interaction Maps (MIMs),
a diagrammatic notation used by biologists. Models of the calculus can be
easily derived from MIM diagrams, for which an unambiguous and executable
interpretation is thus obtained. We give a formal definition of the syntax and
semantics of the MIM calculus, and we study properties of the formalism. A case
study is also presented to show the use of the calculus for modeling
biomolecular networks.Comment: 15 pages; 8 figures; To be published on EPTCS, proceedings of MeCBIC
200
The Statistical Mechanics of Membranes
The fluctuations of two-dimensional extended objects membranes is a rich and
exciting field with many solid results and a wide range of open issues. We
review the distinct universality classes of membranes, determined by the local
order, and the associated phase diagrams. After a discussion of several
physical examples of membranes we turn to the physics of crystalline (or
polymerized) membranes in which the individual monomers are rigidly bound. We
discuss the phase diagram with particular attention to the dependence on the
degree of self-avoidance and anisotropy. In each case we review and discuss
analytic, numerical and experimental predictions of critical exponents and
other key observables. Particular emphasis is given to the results obtained
from the renormalization group epsilon-expansion. The resulting renormalization
group flows and fixed points are illustrated graphically. The full technical
details necessary to perform actual calculations are presented in the
Appendices. We then turn to a discussion of the role of topological defects
whose liberation leads to the hexatic and fluid universality classes. We finish
with conclusions and a discussion of promising open directions for the future.Comment: 75 LaTeX pages, 36 figures. To appear in Physics Reports in the
Proceedings of RG2000, Taxco, 199
Epigenetics in ovarian cancer: premise, properties, and perspectives.
Malignant ovarian tumors bear the highest mortality rate among all gynecological cancers. Both late tumor diagnosis and tolerance to available chemical therapy increase patient mortality. Therefore, it is both urgent and important to identify biomarkers facilitating early identification and novel agents preventing recurrence. Accumulating evidence demonstrates that epigenetic aberrations (particularly histone modifications) are crucial in tumor initiation and development. Histone acetylation and methylation are respectively regulated by acetyltransferases-deacetylases and methyltransferases-demethylases, both of which are implicated in ovarian cancer pathogenesis. In this review, we summarize the most recent discoveries pertaining to ovarian cancer development arising from the imbalance of histone acetylation and methylation, and provide insight into novel therapeutic interventions for the treatment of ovarian carcinoma
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