133 research outputs found
Understanding Health and Disease with Multidimensional Single-Cell Methods
Current efforts in the biomedical sciences and related interdisciplinary
fields are focused on gaining a molecular understanding of health and disease,
which is a problem of daunting complexity that spans many orders of magnitude
in characteristic length scales, from small molecules that regulate cell
function to cell ensembles that form tissues and organs working together as an
organism. In order to uncover the molecular nature of the emergent properties
of a cell, it is essential to measure multiple cell components simultaneously
in the same cell. In turn, cell heterogeneity requires multiple cells to be
measured in order to understand health and disease in the organism. This review
summarizes current efforts towards a data-driven framework that leverages
single-cell technologies to build robust signatures of healthy and diseased
phenotypes. While some approaches focus on multicolor flow cytometry data and
other methods are designed to analyze high-content image-based screens, we
emphasize the so-called Supercell/SVM paradigm (recently developed by the
authors of this review and collaborators) as a unified framework that captures
mesoscopic-scale emergence to build reliable phenotypes. Beyond their specific
contributions to basic and translational biomedical research, these efforts
illustrate, from a larger perspective, the powerful synergy that might be
achieved from bringing together methods and ideas from statistical physics,
data mining, and mathematics to solve the most pressing problems currently
facing the life sciences.Comment: 25 pages, 7 figures; revised version with minor changes. To appear in
J. Phys.: Cond. Mat
Probing Noise in Gene Expression and Protein Production
We derive exact solutions of simplified models for the temporal evolution of
the protein concentration within a cell population arbitrarily far from the
stationary state. We show that monitoring the dynamics can assist in modeling
and understanding the nature of the noise and its role in gene expression and
protein production. We introduce a new measure, the cell turnover distribution,
which can be used to probe the phase of transcription of DNA into messenger
RNA.Comment: 10 pages, 3 figures, supplementary information on reques
Variational approach to protein design and extraction of interaction potentials
We present and discuss a novel approach to the direct and inverse protein
folding problem. The proposed strategy is based on a variational approach that
allows the simultaneous extraction of amino acid interactions and the
low-temperature free energy of sequences of amino acids. The knowledge-based
technique is simple and straightforward to implement even for realistic
off-lattice proteins because it does not entail threading-like procedures. Its
validity is assessed in the context of a lattice model by means of a variety of
stringent checks.Comment: 5 pages, 3 figure
Amino acid classes and the protein folding problem
We present and implement a distance-based clustering of amino acids within
the framework of a statistically derived interaction matrix and show that the
resulting groups faithfully reproduce, for well-designed sequences,
thermodynamic stability in and kinetic accessibility to the native state. A
simple interpretation of the groups is obtained by eigenanalysis of the
interaction matrix.Comment: REVTeX, 11 pages, 4 figures, To appear in J. Chem. Phy
Neutral Theory and Relative Species Abundance in Ecology
The theory of island biogeography[1] asserts that an island or a local
community approaches an equilibrium species richness as a result of the
interplay between the immigration of species from the much larger metacommunity
source area and local extinction of species on the island (local community).
Hubbell[2] generalized this neutral theory to explore the expected steady-state
distribution of relative species abundance (RSA) in the local community under
restricted immigration. Here we present a theoretical framework for the unified
neutral theory of biodiversity[2] and an analytical solution for the
distribution of the RSA both in the metacommunity (Fisher's logseries) and in
the local community, where there are fewer rare species. Rare species are more
extinction-prone, and once they go locally extinct, they take longer to
re-immigrate than do common species. Contrary to recent assertions[3], we show
that the analytical solution provides a better fit, with fewer free parameters,
to the RSA distribution of tree species on Barro Colorado Island (BCI)[4] than
the lognormal distribution[5,6].Comment: 19 pages, 1 figur
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