191 research outputs found
Identifying statistical dependence in genomic sequences via mutual information estimates
Questions of understanding and quantifying the representation and amount of
information in organisms have become a central part of biological research, as
they potentially hold the key to fundamental advances. In this paper, we
demonstrate the use of information-theoretic tools for the task of identifying
segments of biomolecules (DNA or RNA) that are statistically correlated. We
develop a precise and reliable methodology, based on the notion of mutual
information, for finding and extracting statistical as well as structural
dependencies. A simple threshold function is defined, and its use in
quantifying the level of significance of dependencies between biological
segments is explored. These tools are used in two specific applications. First,
for the identification of correlations between different parts of the maize
zmSRp32 gene. There, we find significant dependencies between the 5'
untranslated region in zmSRp32 and its alternatively spliced exons. This
observation may indicate the presence of as-yet unknown alternative splicing
mechanisms or structural scaffolds. Second, using data from the FBI's Combined
DNA Index System (CODIS), we demonstrate that our approach is particularly well
suited for the problem of discovering short tandem repeats, an application of
importance in genetic profiling.Comment: Preliminary version. Final version in EURASIP Journal on
Bioinformatics and Systems Biology. See http://www.hindawi.com/journals/bsb
Scalable Parallel Numerical Constraint Solver Using Global Load Balancing
We present a scalable parallel solver for numerical constraint satisfaction
problems (NCSPs). Our parallelization scheme consists of homogeneous worker
solvers, each of which runs on an available core and communicates with others
via the global load balancing (GLB) method. The parallel solver is implemented
with X10 that provides an implementation of GLB as a library. In experiments,
several NCSPs from the literature were solved and attained up to 516-fold
speedup using 600 cores of the TSUBAME2.5 supercomputer.Comment: To be presented at X10'15 Worksho
LINVIEW: Incremental View Maintenance for Complex Analytical Queries
Many analytics tasks and machine learning problems can be naturally expressed
by iterative linear algebra programs. In this paper, we study the incremental
view maintenance problem for such complex analytical queries. We develop a
framework, called LINVIEW, for capturing deltas of linear algebra programs and
understanding their computational cost. Linear algebra operations tend to cause
an avalanche effect where even very local changes to the input matrices spread
out and infect all of the intermediate results and the final view, causing
incremental view maintenance to lose its performance benefit over
re-evaluation. We develop techniques based on matrix factorizations to contain
such epidemics of change. As a consequence, our techniques make incremental
view maintenance of linear algebra practical and usually substantially cheaper
than re-evaluation. We show, both analytically and experimentally, the
usefulness of these techniques when applied to standard analytics tasks. Our
evaluation demonstrates the efficiency of LINVIEW in generating parallel
incremental programs that outperform re-evaluation techniques by more than an
order of magnitude.Comment: 14 pages, SIGMO
Developed Adomian method for quadratic Kaluza-Klein relativity
We develop and modify the Adomian decomposition method (ADecM) to work for a
new type of nonlinear matrix differential equations (MDE's) which arise in
general relativity (GR) and possibly in other applications. The approach
consists in modifying both the ADecM linear operator with highest order
derivative and ADecM polynomials. We specialize in the case of a 44
nonlinear MDE along with a scalar one describing stationary cylindrically
symmetric metrics in quadratic 5-dimensional GR, derive some of their
properties using ADecM and construct the \textit{most general unique power
series solutions}. However, because of the constraint imposed on the MDE by the
scalar one, the series solutions terminate in closed forms exhausting all
possible solutions.Comment: 17 pages (minor changes in reference [30]
Spatially and temporally synchronized atomic force and total internal reflection fluorescence microscopy for imaging and manipulating cells and biomolecules
Asymptotic equivalence of discretely observed diffusion processes and their Euler scheme: small variance case
This paper establishes the global asymptotic equivalence, in the sense of the
Le Cam -distance, between scalar diffusion models with unknown drift
function and small variance on the one side, and nonparametric autoregressive
models on the other side. The time horizon is kept fixed and both the cases
of discrete and continuous observation of the path are treated. We allow non
constant diffusion coefficient, bounded but possibly tending to zero. The
asymptotic equivalences are established by constructing explicit equivalence
mappings.Comment: 21 page
Self-interrupted synthesis of sterically hindered aliphatic polyamide dendrimers
Hydrolytically and enzymatically stable nanoscale synthetic constructs, with well-defined structures that exhibit antimicrobial activity, offer exciting possibilities for diverse applications in the emerging field of nanomedicine. Herein, we demonstrate that it is the core conformation, rather than periodicity, that ultimately controls the synthesis of sterically hindered aliphatic polyamide dendrimers. The latter self-interrupt at a predictable low generation number due to backfolding of their peripheral groups, which in turn leads to well-defined nanoarchitectures
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