Search results for "soft"

Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy

2017

Neuronal networks are often characterized by their spiking and bursting statistics. Previously, we introducedan adaptive burst analysis methodwhich enhances the analysis power for neuronal networks with highly varying firing dynamics. The adaptation is based on single channels analyzing each element of a network separately. Such kind of analysis was adequate for the assessment of local behavior, where the analysis focuses on the neuronal activity in the vicinity of a single electrode. However, the assessment of the whole network may be hampered, if parts of the network are analyzed using different rules. Here, we test how using multiple channels and measurement time points affect adaptive b…

A new parallel pipeline for DNA methylation analysis of long reads datasets

2017

Background DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis have been proposed over recent years. However, the current trend is that the new sequencers and the ones expected for an upcoming future yield sequences of increasing length, making these software tools inefficient and obsolete. Results In this paper, we propose a new software based on a strategy for methylation analysis of Methyl-seq sequencing data that requires much shorter execution times while…

2019

As rats learn to search for multiple sources of food or water in a complex environment, they generate increasingly efficient trajectories between reward sites. Such spatial navigation capacity involves the replay of hippocampal place-cells during awake states, generating small sequences of spatially related place-cell activity that we call "snippets". These snippets occur primarily during sharp-wave-ripples (SWRs). Here we focus on the role of such replay events, as the animal is learning a traveling salesperson task (TSP) across multiple trials. We hypothesize that snippet replay generates synthetic data that can substantially expand and restructure the experience available and make learni…

miRToolsGallery: a tag-based and rankable microRNA bioinformatics resources database portal

2017

Abstract Hundreds of bioinformatics tools have been developed for MicroRNA (miRNA) investigations including those used for identification, target prediction, structure and expression profile analysis. However, finding the correct tool for a specific application requires the tedious and laborious process of locating, downloading, testing and validating the appropriate tool from a group of nearly a thousand. In order to facilitate this process, we developed a novel database portal named miRToolsGallery. We constructed the portal by manually curating > 950 miRNA analysis tools and resources. In the portal, a query to locate the appropriate tool is expedited by being searchable, filterable and …

Revealing community structures by ensemble clustering using group diffusion

2018

We propose an ensemble clustering approach using group diffusion to reveal community structures in data. We represent data points as a directed graph and assume each data point belong to single cluster membership instead of multiple memberships. The method is based on the concept of ensemble group diffusion with a parameter to represent diffusion depth in clustering. The ability to modulate the diffusion-depth parameter by varying it within a certain interval allows for more accurate construction of clusters. Depending on the value of the diffusion-depth parameter, the presented approach can determine very well both local clusters and global structure of data. At the same time, the ability …

SpCLUST: Towards a fast and reliable clustering for potentially divergent biological sequences

2019

International audience; This paper presents SpCLUST, a new C++ package that takes a list of sequences as input, aligns them with MUSCLE, computes their similarity matrix in parallel and then performs the clustering. SpCLUST extends a previously released software by integrating additional scoring matrices which enables it to cover the clustering of amino-acid sequences. The similarity matrix is now computed in parallel according to the master/slave distributed architecture, using MPI. Performance analysis, realized on two real datasets of 100 nucleotide sequences and 1049 amino-acids ones, show that the resulting library substantially outperforms the original Python package. The proposed pac…

Rocker: Open source, easy-to-use tool for AUC and enrichment calculations and ROC visualization

2016

Receiver operating characteristics (ROC) curve with the calculation of area under curve (AUC) is a useful tool to evaluate the performance of biomedical and chemoinformatics data. For example, in virtual drug screening ROC curves are very often used to visualize the efficiency of the used application to separate active ligands from inactive molecules. Unfortunately, most of the available tools for ROC analysis are implemented into commercially available software packages, or are plugins in statistical software, which are not always the easiest to use. Here, we present Rocker, a simple ROC curve visualization tool that can be used for the generation of publication quality images. Rocker also…

Principal components analysis: theory and application to gene expression data analysis

2018

Advances in computational power have enabled research to generate significant amounts of data related to complex biological problems. Consequently, applying appropriate data analysis techniques has become paramount to tackle this complexity. However, theoretical understanding of statistical methods is necessary to ensure that the correct method is used and that sound inferences are made based on the analysis. In this article, we elaborate on the theory behind principal components analysis (PCA), which has become a favoured multivariate statistical tool in the field of omics-data analysis. We discuss the necessary prerequisites and steps to produce statistically valid results and provide gui…

Deep Learning Architectures for DNA Sequence Classification

2017

DNA sequence classification is a key task in a generic computational framework for biomedical data analysis, and in recent years several machine learning technique have been adopted to successful accomplish with this task. Anyway, the main difficulty behind the problem remains the feature selection process. Sequences do not have explicit features, and the commonly used representations introduce the main drawback of the high dimensionality. For sure, machine learning method devoted to supervised classification tasks are strongly dependent on the feature extraction step, and in order to build a good representation it is necessary to recognize and measure meaningful details of the items to cla…

On the Use of Binary Trees for DNA Hydroxymethylation Analysis

2017

DNA methylation (mC) and hydroxymethylation (hmC) can have a significant effect on normal human development, health and disease status. Hydroxymethylation studies require specific treatment of DNA, as well as software tools for their analysis. In this paper, we propose a parallel software tool for analyzing the DNA hydroxymethylation data obtained by TAB-seq. The software is based on the use of binary trees for searching the different occurrences of methylation and hydroxymethylation in DNA samples. The binary trees allow to efficiently store and access the information about the methylation of each methylated/hydroxymethylated cytosines in the samples. Evaluation results shows that the perf…