Improved Spike-Timed Mappings using a Tri-Phasic Spike Timing-Dependent Plasticity Rule

Reservoir computing and the liquid state machine models have received much attention in the literature in recent years. In this paper we investigate using a reservoir composed of a network of spiking neurons, with synaptic delays, whose synapses are allowed to evolve using a tri-phasic spike timing- dependent plasticity (STDP) rule. The networks are trained to produce specific spike trains in response to spatio-temporal input patterns. The results of using a tri-phasic STDP rule on the network properties are compared to those found using the more common exponential form of the rule. It is found that each rule causes the synaptic weights to evolve in significantly different fashions giving rise to different network dynamics. It is also found that the networks evolved with the tri-phasic rule are more capable of mapping input spatio-temporal patterns to the output spike trains

Two Avenues to Self-Interaction Correction within Kohn-Sham Theory: Unitary Invariance is the Shortcut

The most widely-used density functionals for the exchange-correlation energy are inexact for one-electron systems. Their self-interaction errors can be severe in some applications. The problem is not only to correct the self-interaction error, but to do so in a way that will not violate size-consistency and will not go outside the standard Kohn-Sham density functional theory. The solution via the optimized effective potential (OEP) method will be discussed, first for the Perdew-Zunger self-interaction correction (whose performance for molecules is briefly summarized) and then for the more modern self-interaction corrections based upon unitarily-invariant indicators of iso-orbital regions. For the latter approaches, the OEP construction is greatly simplified. The kinetic-energy-based iso-orbital indicator \tau^W_\sigma(\re)/\tau_\sigma(\re) will be discussed and plotted, along with an alternative exchange-based indicator

Strategies for analyzing bisulfite sequencing data

DNA methylation is one of the main epigenetic modifications in the eukaryotic genome; it has been shown to play a role in cell-type specific regulation of gene expression, and therefore cell-type identity. Bisulfite sequencing is the gold-standard for measuring methylation over the genomes of interest. Here, we review several techniques used for the analysis of high-throughput bisulfite sequencing. We introduce specialized short-read alignment techniques as well as pre/post-alignment quality check methods to ensure data quality. Furthermore, we discuss subsequent analysis steps after alignment. We introduce various differential methylation methods and compare their performance using simulated and real bisulfite sequencing datasets. We also discuss the methods used to segment methylomes in order to pinpoint regulatory regions. We introduce annotation methods that can be used for further classification of regions returned by segmentation and differential methylation methods. Finally, we review software packages that implement strategies to efficiently deal with large bisulfite sequencing datasets locally and we discuss online analysis workflows that do not require any prior programming skills. The analysis strategies described in this review will guide researchers at any level to the best practices of bisulfite sequencing analysis

Reference time in SpikeProp

Although some studies have been done on the learning algorithm for spiking neural networks SpikeProp, little has been mentioned about the required input bias neuron that sets the reference time start. This paper examines the importance of the reference time in neural networks based on temporal encoding. The findings refute previous assumptions about the reference start time

Inhibition of triosephosphate isomerase by phosphoenolpyruvate in the feedback-regulation of glycolysis.

The inhibition of triosephosphate isomerase (TPI) in glycolysis by the pyruvate kinase (PK) substrate phosphoenolpyruvate (PEP) results in a newly discovered feedback loop that counters oxidative stress in cancer and actively respiring cells. The mechanism underlying this inhibition is illuminated by the co-crystal structure of TPI with bound PEP at 1.6 Å resolution, and by mutational studies guided by the crystallographic results. PEP is bound to the catalytic pocket of TPI and occludes substrate, which accounts for the observation that PEP competitively inhibits the interconversion of glyceraldehyde-3-phosphate and dihydroxyacetone phosphate. Replacing an isoleucine residue located in the catalytic pocket of TPI with valine or threonine altered binding of substrates and PEP, reducing TPI activity in vitro and in vivo. Confirming a TPI-mediated activation of the pentose phosphate pathway (PPP), transgenic yeast cells expressing these TPI mutations accumulate greater levels of PPP intermediates and have altered stress resistance, mimicking the activation of the PK-TPI feedback loop. These results support a model in which glycolytic regulation requires direct catalytic inhibition of TPI by the pyruvate kinase substrate PEP, mediating a protective metabolic self-reconfiguration of central metabolism under conditions of oxidative stress

The emergence of polychronous groups under varying input patterns, plasticity rules and network connectivities

Polychronous groups are unique temporal patterns of neural activity that exist implicitly within non-linear, recur- rently connected networks. Through Hebbian based learning these groups can be strengthened to give rise to larger chains of spatiotemporal activity. Compared to other structures such as Synfire chains, they have demonstrated the potential of a much larger capacity for memory or computation within spiking neural networks. Polychronous groups are believed to relate to the input signals under which they emerge. Here we investigate the quantity of groups that emerge from increasing numbers of repeating input patterns, whilst also comparing the differences between two plasticity rules and two network connectivities. We find – perhaps counter-intuitively – that fewer groups are formed as the number of repeating input patterns increases. Furthermore, we find that a tri-phasic learning rule gives rise to fewer groups than the ’classical’ double decaying exponential STDP plasticity window. It is also found that a scale-free network structure produces a similar quantity, but generally smaller groups than a randomly connected Erdös-Rényi structur

Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology

The Galaxy Project offers the popular web browser-based platform Galaxy for running bioinformatics tools and constructing simple workflows. Here, we present a broad collection of additional Galaxy tools for large scale analysis of gene and protein sequences. The motivating research theme is the identification of specific genes of interest in a range of non-model organisms, and our central example is the identification and prediction of "effector" proteins produced by plant pathogens in order to manipulate their host plant. This functional annotation of a pathogen's predicted capacity for virulence is a key step in translating sequence data into potential applications in plant pathology. This collection includes novel tools, and widely-used third-party tools such as NCBI BLASTC wrapped for use within Galaxy. Individual bioinformatics software tools are typically available separately as standalone packages, or in online browserbased form. The Galaxy framework enables the user to combine these and other tools to automate organism scale analyses as workflows, without demanding familiarity with command line tools and scripting.Workflows created using Galaxy can be saved and are reusable, so may be distributed within and between research groups, facilitating the construction of a set of standardised, reusable bioinformatic protocols. The Galaxy tools and workflows described in this manuscript are open source and freely available from the Galaxy Tool Shed (http://usegalaxy.org/toolshed or http://toolshed.g2.bx.psu.edu)

Alteration of the Route to Menaquinone towards Isochorismate-Derived Metabolites

Chorismate and isochorismate constitute branch-point intermediates in the biosynthesis of many aromatic metabolites in microorganisms and plants. To obtain unnatural compounds, we modified the route to menaquinone in Escherichia coli. We propose a model for the binding of isochorismate to the active site of MenD ((1R,2S, 5S,6S)-2-succinyl-5-enolpyruvyl-6-hydroxycyclohex-3-ene-1-carboxylate (SEPHCHC) synthase) that explains the outcome of the native reaction with α-ketoglutarate. We have rationally designed variants of MenD for the conversion of several isochorismate analogues. The double-variant Asn117Arg–Leu478Thr preferentially converts (5S,6S)-5,6-dihydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHD), the hydrolysis product of isochorismate, with a >70-fold higher ratio than that for the wild type. The single-variant Arg107Ile uses (5S,6S)-6-amino-5-hydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHA) as substrate with >6-fold conversion compared to wild-type MenD. The novel compounds have been made accessible in vivo (up to 5.3 g L−1). Unexpectedly, as the identified residues such as Arg107 are highly conserved (>94 %), some of the designed variations can be found in wild-type SEPHCHC synthases from other bacteria (Arg107Lys, 0.3 %). This raises the question for the possible natural occurrence of as yet unexplored branches of the shikimate pathway.Fil: Fries, Alexander Erich. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina. Albert Ludwigs University of Freiburg; AlemaniaFil: Mazzaferro, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina. Albert Ludwigs University of Freiburg; AlemaniaFil: Grüning, Björn. Albert Ludwigs University of Freiburg; AlemaniaFil: Bisel, Philippe. Albert Ludwigs University of Freiburg; AlemaniaFil: Stibal, Karin. Albert Ludwigs University of Freiburg; AlemaniaFil: Buchholz, Patrick C. F.. University of Stuttgart; AlemaniaFil: Pleiss, Jürgen. Universität Stuttgart;Fil: Sprenger, Georg A.. Universität Stuttgart;Fil: Müller, Michael. Albert Ludwigs University of Freiburg; Alemani

The RNA workbench: best practices for RNA and high-throughput sequencing bioinformatics in Galaxy

RNA-based regulation has become a major research topic in molecular biology. The analysis of epigenetic and expression data is therefore incomplete if RNA-based regulation is not taken into account. Thus, it is increasingly important but not yet standard to combine RNA-centric data and analysis tools with other types of experimental data such as RNA-seq or ChIP-seq. Here, we present the RNA workbench, a comprehensive set of analysis tools and consolidated workflows that enable the researcher to combine these two worlds. Based on the Galaxy framework the workbench guarantees simple access, easy extension, flexible adaption to personal and security needs, and sophisticated analyses that are independent of command-line knowledge. Currently, it includes more than 50 bioinformatics tools that are dedicated to different research areas of RNA biology including RNA structure analysis, RNA alignment, RNA annotation, RNA-protein interaction, ribosome profiling, RNA-seq analysis and RNA target prediction. The workbench is developed and maintained by experts in RNA bioinformatics and the Galaxy framework. Together with the growing community evolving around this workbench, we are committed to keep the workbench up-to-date for future standards and needs, providing researchers with a reliable and robust framework for RNA data analysis. Availability: The RNA workbench is available at https://github.com/bgruening/galaxy-rna-workbench