180 research outputs found
Colonyzer: automated quantification of micro-organism growth characteristics on solid agar
<p>Abstract</p> <p>Background</p> <p>High-throughput screens comparing growth rates of arrays of distinct micro-organism cultures on solid agar are useful, rapid methods of quantifying genetic interactions. Growth rate is an informative phenotype which can be estimated by measuring cell densities at one or more times after inoculation. Precise estimates can be made by inoculating cultures onto agar and capturing cell density frequently by plate-scanning or photography, especially throughout the exponential growth phase, and summarising growth with a simple dynamic model (e.g. the logistic growth model). In order to parametrize such a model, a robust image analysis tool capable of capturing a wide range of cell densities from plate photographs is required.</p> <p>Results</p> <p>Colonyzer is a collection of image analysis algorithms for automatic quantification of the size, granularity, colour and location of micro-organism cultures grown on solid agar. Colonyzer is uniquely sensitive to extremely low cell densities photographed after dilute liquid culture inoculation (spotting) due to image segmentation using a mixed Gaussian model for plate-wide thresholding based on pixel intensity. Colonyzer is robust to slight experimental imperfections and corrects for lighting gradients which would otherwise introduce spatial bias to cell density estimates without the need for imaging dummy plates. Colonyzer is general enough to quantify cultures growing in any rectangular array format, either growing after pinning with a dense inoculum or growing with the irregular morphology characteristic of spotted cultures. Colonyzer was developed using the open source packages: Python, RPy and the Python Imaging Library and its source code and documentation are available on SourceForge under GNU General Public License. Colonyzer is adaptable to suit specific requirements: e.g. automatic detection of cultures at irregular locations on streaked plates for robotic picking, or decreasing analysis time by disabling components such as lighting correction or colour measures.</p> <p>Conclusion</p> <p>Colonyzer can automatically quantify culture growth from large batches of captured images of microbial cultures grown during genome-wide scans over the wide range of cell densities observable after highly dilute liquid spot inoculation, as well as after more concentrated pinning inoculation. Colonyzer is open-source, allowing users to assess it, adapt it to particular research requirements and to contribute to its development.</p
interPopula: a Python API to access the HapMap Project dataset
<p>Abstract</p> <p>Background</p> <p>The HapMap project is a publicly available catalogue of common genetic variants that occur in humans, currently including several million SNPs across 1115 individuals spanning 11 different populations. This important database does not provide any programmatic access to the dataset, furthermore no standard relational database interface is provided.</p> <p>Results</p> <p>interPopula is a Python API to access the HapMap dataset. interPopula provides integration facilities with both the Python ecology of software (e.g. Biopython and matplotlib) and other relevant human population datasets (e.g. Ensembl gene annotation and UCSC Known Genes). A set of guidelines and code examples to address possible inconsistencies across heterogeneous data sources is also provided.</p> <p>Conclusions</p> <p>interPopula is a straightforward and flexible Python API that facilitates the construction of scripts and applications that require access to the HapMap dataset.</p
Assessing Levels of Attention Using Low Cost Eye Tracking
The emergence of mobile eye trackers embedded in next generation smartphones
or VR displays will make it possible to trace not only what objects we look at
but also the level of attention in a given situation. Exploring whether we can
quantify the engagement of a user interacting with a laptop, we apply mobile
eye tracking in an in-depth study over 2 weeks with nearly 10.000 observations
to assess pupil size changes, related to attentional aspects of alertness,
orientation and conflict resolution. Visually presenting conflicting cues and
targets we hypothesize that it's feasible to measure the allocated effort when
responding to confusing stimuli. Although such experiments are normally carried
out in a lab, we are able to differentiate between sustained alertness and
complex decision making even with low cost eye tracking "in the wild". From a
quantified self perspective of individual behavioral adaptation, the
correlations between the pupil size and the task dependent reaction time and
error rates may longer term provide a foundation for modifying smartphone
content and interaction to the users perceived level of attention.Comment: 12 pages, 6 figures, 2 tables. The final publication will be
available at Springer via http://dx.doi.org/DOIxxx, when published as part of
the HCI International 2016 Conference Proceeding
Bistability in Apoptosis by Receptor Clustering
Apoptosis is a highly regulated cell death mechanism involved in many
physiological processes. A key component of extrinsically activated apoptosis
is the death receptor Fas, which, on binding to its cognate ligand FasL,
oligomerize to form the death-inducing signaling complex. Motivated by recent
experimental data, we propose a mathematical model of death ligand-receptor
dynamics where FasL acts as a clustering agent for Fas, which form locally
stable signaling platforms through proximity-induced receptor interactions.
Significantly, the model exhibits hysteresis, providing an upstream mechanism
for bistability and robustness. At low receptor concentrations, the bistability
is contingent on the trimerism of FasL. Moreover, irreversible bistability,
representing a committed cell death decision, emerges at high concentrations,
which may be achieved through receptor pre-association or localization onto
membrane lipid rafts. Thus, our model provides a novel theory for these
observed biological phenomena within the unified context of bistability.
Importantly, as Fas interactions initiate the extrinsic apoptotic pathway, our
model also suggests a mechanism by which cells may function as bistable
life/death switches independently of any such dynamics in their downstream
components. Our results highlight the role of death receptors in deciding cell
fate and add to the signal processing capabilities attributed to receptor
clustering.Comment: Accepted by PLoS Comput Bio
Information transmission in oscillatory neural activity
Periodic neural activity not locked to the stimulus or to motor responses is
usually ignored. Here, we present new tools for modeling and quantifying the
information transmission based on periodic neural activity that occurs with
quasi-random phase relative to the stimulus. We propose a model to reproduce
characteristic features of oscillatory spike trains, such as histograms of
inter-spike intervals and phase locking of spikes to an oscillatory influence.
The proposed model is based on an inhomogeneous Gamma process governed by a
density function that is a product of the usual stimulus-dependent rate and a
quasi-periodic function. Further, we present an analysis method generalizing
the direct method (Rieke et al, 1999; Brenner et al, 2000) to assess the
information content in such data. We demonstrate these tools on recordings from
relay cells in the lateral geniculate nucleus of the cat.Comment: 18 pages, 8 figures, to appear in Biological Cybernetic
A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems
In this paper we present a methodological framework that meets novel
requirements emerging from upcoming types of accelerated and highly
configurable neuromorphic hardware systems. We describe in detail a device with
45 million programmable and dynamic synapses that is currently under
development, and we sketch the conceptual challenges that arise from taking
this platform into operation. More specifically, we aim at the establishment of
this neuromorphic system as a flexible and neuroscientifically valuable
modeling tool that can be used by non-hardware-experts. We consider various
functional aspects to be crucial for this purpose, and we introduce a
consistent workflow with detailed descriptions of all involved modules that
implement the suggested steps: The integration of the hardware interface into
the simulator-independent model description language PyNN; a fully automated
translation between the PyNN domain and appropriate hardware configurations; an
executable specification of the future neuromorphic system that can be
seamlessly integrated into this biology-to-hardware mapping process as a test
bench for all software layers and possible hardware design modifications; an
evaluation scheme that deploys models from a dedicated benchmark library,
compares the results generated by virtual or prototype hardware devices with
reference software simulations and analyzes the differences. The integration of
these components into one hardware-software workflow provides an ecosystem for
ongoing preparative studies that support the hardware design process and
represents the basis for the maturity of the model-to-hardware mapping
software. The functionality and flexibility of the latter is proven with a
variety of experimental results
LNCS
A controller is a device that interacts with a plant. At each time point,it reads the plant’s state and issues commands with the goal that the plant oper-ates optimally. Constructing optimal controllers is a fundamental and challengingproblem. Machine learning techniques have recently been successfully applied totrain controllers, yet they have limitations. Learned controllers are monolithic andhard to reason about. In particular, it is difficult to add features without retraining,to guarantee any level of performance, and to achieve acceptable performancewhen encountering untrained scenarios. These limitations can be addressed bydeploying quantitative run-timeshieldsthat serve as a proxy for the controller.At each time point, the shield reads the command issued by the controller andmay choose to alter it before passing it on to the plant. We show how optimalshields that interfere as little as possible while guaranteeing a desired level ofcontroller performance, can be generated systematically and automatically usingreactive synthesis. First, we abstract the plant by building a stochastic model.Second, we consider the learned controller to be a black box. Third, we mea-surecontroller performanceandshield interferenceby two quantitative run-timemeasures that are formally defined using weighted automata. Then, the problemof constructing a shield that guarantees maximal performance with minimal inter-ference is the problem of finding an optimal strategy in a stochastic2-player game“controller versus shield” played on the abstract state space of the plant with aquantitative objective obtained from combining the performance and interferencemeasures. We illustrate the effectiveness of our approach by automatically con-structing lightweight shields for learned traffic-light controllers in various roadnetworks. The shields we generate avoid liveness bugs, improve controller per-formance in untrained and changing traffic situations, and add features to learnedcontrollers, such as giving priority to emergency vehicles
Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data
Demographic models built from genetic data play important roles in
illuminating prehistorical events and serving as null models in genome scans
for selection. We introduce an inference method based on the joint frequency
spectrum of genetic variants within and between populations. For candidate
models we numerically compute the expected spectrum using a diffusion
approximation to the one-locus two-allele Wright-Fisher process, involving up
to three simultaneous populations. Our approach is a composite likelihood
scheme, since linkage between neutral loci alters the variance but not the
expectation of the frequency spectrum. We thus use bootstraps incorporating
linkage to estimate uncertainties for parameters and significance values for
hypothesis tests. Our method can also incorporate selection on single sites,
predicting the joint distribution of selected alleles among populations
experiencing a bevy of evolutionary forces, including expansions, contractions,
migrations, and admixture. As applications, we model human expansion out of
Africa and the settlement of the New World, using 5 Mb of noncoding DNA
resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by
the Environmental Genome Project. We also combine our demographic model with a
previously estimated distribution of selective effects among newly arising
amino acid mutations to accurately predict the frequency spectrum of
nonsynonymous variants across three continental populations (YRI, CHB, CEU).Comment: 17 pages, 4 figures, supporting information included with sourc
Review of Inverse Laplace Transform Algorithms for Laplace-Space Numerical Approaches
A boundary element method (BEM) simulation is used to compare the efficiency
of numerical inverse Laplace transform strategies, considering general
requirements of Laplace-space numerical approaches. The two-dimensional BEM
solution is used to solve the Laplace-transformed diffusion equation, producing
a time-domain solution after a numerical Laplace transform inversion. Motivated
by the needs of numerical methods posed in Laplace-transformed space, we
compare five inverse Laplace transform algorithms and discuss implementation
techniques to minimize the number of Laplace-space function evaluations. We
investigate the ability to calculate a sequence of time domain values using the
fewest Laplace-space model evaluations. We find Fourier-series based inversion
algorithms work for common time behaviors, are the most robust with respect to
free parameters, and allow for straightforward image function evaluation re-use
across at least a log cycle of time
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