21,499 research outputs found
Abnormal cognition, sleep, EEG and brain metabolism in a novel knock-in Alzheimer mouse, PLB1
Peer reviewedPublisher PD
Erwin Schroedinger, Francis Crick and epigenetic stability
Schroedinger's book 'What is Life?' is widely credited for having played a
crucial role in development of molecular and cellular biology. My essay
revisits the issues raised by this book from the modern perspective of
epigenetics and systems biology. I contrast two classes of potential mechanisms
of epigenetic stability: 'epigenetic templating' and 'systems biology'
approaches, and consider them from the point of view expressed by Schroedinger.
I also discuss how quantum entanglement, a nonclassical feature of quantum
mechanics, can help to address the 'problem of small numbers' that lead
Schroedinger to promote the idea of molecular code-script for explanation of
stability of biological order.Comment: New and improved version of the essay, now published in the online
journal 'Biology Direct'. Contains more expanded discussion on entanglement.
18 pages, 2 figures. The file includes open reviews by E.Koonin, V.Vedral and
E.Karsent
Using distributional similarity to organise biomedical terminology
We investigate an application of distributional similarity techniques to the problem of structural organisation of biomedical terminology. Our application domain is the relatively small GENIA corpus. Using terms that have been accurately marked-up by hand within the corpus, we consider the problem of automatically determining semantic proximity. Terminological units are dened for our purposes as normalised classes of individual terms. Syntactic analysis of the corpus data is carried out using the Pro3Gres parser and provides the data required to calculate distributional similarity using a variety of dierent measures. Evaluation is performed against a hand-crafted gold standard for this domain in the form of the GENIA ontology. We show that distributional similarity can be used to predict semantic type with a good degree of accuracy
Introduction to protein folding for physicists
The prediction of the three-dimensional native structure of proteins from the
knowledge of their amino acid sequence, known as the protein folding problem,
is one of the most important yet unsolved issues of modern science. Since the
conformational behaviour of flexible molecules is nothing more than a complex
physical problem, increasingly more physicists are moving into the study of
protein systems, bringing with them powerful mathematical and computational
tools, as well as the sharp intuition and deep images inherent to the physics
discipline. This work attempts to facilitate the first steps of such a
transition. In order to achieve this goal, we provide an exhaustive account of
the reasons underlying the protein folding problem enormous relevance and
summarize the present-day status of the methods aimed to solving it. We also
provide an introduction to the particular structure of these biological
heteropolymers, and we physically define the problem stating the assumptions
behind this (commonly implicit) definition. Finally, we review the 'special
flavor' of statistical mechanics that is typically used to study the
astronomically large phase spaces of macromolecules. Throughout the whole work,
much material that is found scattered in the literature has been put together
here to improve comprehension and to serve as a handy reference.Comment: 53 pages, 18 figures, the figures are at a low resolution due to
arXiv restrictions, for high-res figures, go to http://www.pabloechenique.co
Multi-Target Prediction: A Unifying View on Problems and Methods
Multi-target prediction (MTP) is concerned with the simultaneous prediction
of multiple target variables of diverse type. Due to its enormous application
potential, it has developed into an active and rapidly expanding research field
that combines several subfields of machine learning, including multivariate
regression, multi-label classification, multi-task learning, dyadic prediction,
zero-shot learning, network inference, and matrix completion. In this paper, we
present a unifying view on MTP problems and methods. First, we formally discuss
commonalities and differences between existing MTP problems. To this end, we
introduce a general framework that covers the above subfields as special cases.
As a second contribution, we provide a structured overview of MTP methods. This
is accomplished by identifying a number of key properties, which distinguish
such methods and determine their suitability for different types of problems.
Finally, we also discuss a few challenges for future research
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