64,949 research outputs found
SLIDER: Mining correlated motifs in protein-protein interaction networks
Abstract—Correlated motif mining (CMM) is the problem to find overrepresented pairs of patterns, called motif pairs, in interacting protein sequences. Algorithmic solutions for CMM thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that CMM is an NP-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the method SLIDER which uses local search with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that SLIDER outperforms existing motif-driven CMM methods and scales to large protein-protein interaction networks
Implementation and performance of SIBYLS: a dual endstation small-angle X-ray scattering and macromolecular crystallography beamline at the Advanced Light Source.
The SIBYLS beamline (12.3.1) of the Advanced Light Source at Lawrence Berkeley National Laboratory, supported by the US Department of Energy and the National Institutes of Health, is optimized for both small-angle X-ray scattering (SAXS) and macromolecular crystallography (MX), making it unique among the world's mostly SAXS or MX dedicated beamlines. Since SIBYLS was commissioned, assessments of the limitations and advantages of a combined SAXS and MX beamline have suggested new strategies for integration and optimal data collection methods and have led to additional hardware and software enhancements. Features described include a dual mode monochromator [containing both Si(111) crystals and Mo/B(4)C multilayer elements], rapid beamline optics conversion between SAXS and MX modes, active beam stabilization, sample-loading robotics, and mail-in and remote data collection. These features allow users to gain valuable insights from both dynamic solution scattering and high-resolution atomic diffraction experiments performed at a single synchrotron beamline. Key practical issues considered for data collection and analysis include radiation damage, structural ensembles, alternative conformers and flexibility. SIBYLS develops and applies efficient combined MX and SAXS methods that deliver high-impact results by providing robust cost-effective routes to connect structures to biology and by performing experiments that aid beamline designs for next generation light sources
Symbol Synchronization for Diffusive Molecular Communication Systems
Symbol synchronization refers to the estimation of the start of a symbol
interval and is needed for reliable detection. In this paper, we develop a
symbol synchronization framework for molecular communication (MC) systems where
we consider some practical challenges which have not been addressed in the
literature yet. In particular, we take into account that in MC systems, the
transmitter may not be equipped with an internal clock and may not be able to
emit molecules with a fixed release frequency. Such restrictions hold for
practical nanotransmitters, e.g. modified cells, where the lengths of the
symbol intervals may vary due to the inherent randomness in the availability of
food and energy for molecule generation, the process for molecule production,
and the release process. To address this issue, we propose to employ two types
of molecules, one for synchronization and one for data transmission. We derive
the optimal maximum likelihood (ML) symbol synchronization scheme as a
performance upper bound. Since ML synchronization entails high complexity, we
also propose two low-complexity synchronization schemes, namely a peak
observation-based scheme and a threshold-trigger scheme, which are suitable for
MC systems with limited computational capabilities. Our simulation results
reveal the effectiveness of the proposed synchronization~schemes and suggest
that the end-to-end performance of MC systems significantly depends on the
accuracy of symbol synchronization.Comment: This paper has been accepted for presentation at IEEE International
Conference on Communications (ICC) 201
Emulating Non-Abelian Topological Matter in Cold Atom Optical Lattices
Certain proposed extended Bose-Hubbard models may exhibit topologically
ordered ground states with excitations obeying non-Abelian braid statistics. A
sufficient tuning of Hubbard parameters could yield excitation braiding rules
allowing implementation of a universal set of topologically protected quantum
gates. We discuss potential difficulties in realizing a model with a proposed
non-Abelian topologically ordered ground state using optical lattices
containing bosonic dipoles. Our direct implementation scheme does not realize
the necessary anisotropic hopping, anisotropic interactions, and low
temperatures
Quantifying the benefits of vehicle pooling with shareability networks
Taxi services are a vital part of urban transportation, and a considerable
contributor to traffic congestion and air pollution causing substantial adverse
effects on human health. Sharing taxi trips is a possible way of reducing the
negative impact of taxi services on cities, but this comes at the expense of
passenger discomfort quantifiable in terms of a longer travel time. Due to
computational challenges, taxi sharing has traditionally been approached on
small scales, such as within airport perimeters, or with dynamical ad-hoc
heuristics. However, a mathematical framework for the systematic understanding
of the tradeoff between collective benefits of sharing and individual passenger
discomfort is lacking. Here we introduce the notion of shareability network
which allows us to model the collective benefits of sharing as a function of
passenger inconvenience, and to efficiently compute optimal sharing strategies
on massive datasets. We apply this framework to a dataset of millions of taxi
trips taken in New York City, showing that with increasing but still relatively
low passenger discomfort, cumulative trip length can be cut by 40% or more.
This benefit comes with reductions in service cost, emissions, and with split
fares, hinting towards a wide passenger acceptance of such a shared service.
Simulation of a realistic online system demonstrates the feasibility of a
shareable taxi service in New York City. Shareability as a function of trip
density saturates fast, suggesting effectiveness of the taxi sharing system
also in cities with much sparser taxi fleets or when willingness to share is
low.Comment: Main text: 6 pages, 3 figures, SI: 24 page
TREEOME: A framework for epigenetic and transcriptomic data integration to explore regulatory interactions controlling transcription
Motivation: Predictive modelling of gene expression is a powerful framework
for the in silico exploration of transcriptional regulatory interactions
through the integration of high-throughput -omics data. A major limitation of
previous approaches is their inability to handle conditional and synergistic
interactions that emerge when collectively analysing genes subject to different
regulatory mechanisms. This limitation reduces overall predictive power and
thus the reliability of downstream biological inference.
Results: We introduce an analytical modelling framework (TREEOME: tree of
models of expression) that integrates epigenetic and transcriptomic data by
separating genes into putative regulatory classes. Current predictive modelling
approaches have found both DNA methylation and histone modification epigenetic
data to provide little or no improvement in accuracy of prediction of
transcript abundance despite, for example, distinct anti-correlation between
mRNA levels and promoter-localised DNA methylation. To improve on this, in
TREEOME we evaluate four possible methods of formulating gene-level DNA
methylation metrics, which provide a foundation for identifying gene-level
methylation events and subsequent differential analysis, whereas most previous
techniques operate at the level of individual CpG dinucleotides. We demonstrate
TREEOME by integrating gene-level DNA methylation (bisulfite-seq) and histone
modification (ChIP-seq) data to accurately predict genome-wide mRNA transcript
abundance (RNA-seq) for H1-hESC and GM12878 cell lines.
Availability: TREEOME is implemented using open-source software and made
available as a pre-configured bootable reference environment. All scripts and
data presented in this study are available online at
http://sourceforge.net/projects/budden2015treeome/.Comment: 14 pages, 6 figure
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