Search results for "software"

Discriminating graph pattern mining from gene expression data

2016

We consider the problem of mining gene expression data in order to single out interesting features that characterize healthy/unhealthy samples of an input dataset. We present and approach based on a network model of the input gene expression data, where there is a labelled graph for each sample. To the best of our knowledge, this is the first attempt to build a different graph for each sample and, then, to have a database of graphs for representing a sample set. Out main goal is that of singling out interesting differences between healthy and unhealthy samples, through the extraction of "discriminating patterns" among graphs belonging to the two different sample sets. Differently from the …

Applying Conceptual Modeling to Better Understand the Human Genome

2016

The objective of the work is to present the benefits of the application of Conceptual Modeling (CM) in complex domains, such as genomics. This paper explains the evolution of a Conceptual Schema of the Human Genome (CSHG), which seeks to provide a clear and precise understanding of the human genome. We want to highlighting all the advantages of the application of CM in a complex domain such as Genomic Information Systems (GeIS). We show how over time this model has evolved, thus we have discovered better forms of representation. As we advanced in exploring the domain, we understood that we should be extending and incorporating the new concepts detected into our model. Here we present and di…

HPG pore: an efficient and scalable framework for nanopore sequencing data.

2016

The use of nanopore technologies is expected to spread in the future because they are portable and can sequence long fragments of DNA molecules without prior amplification. The first nanopore sequencer available, the MinION™ from Oxford Nanopore Technologies, is a USB-connected, portable device that allows real-time DNA analysis. In addition, other new instruments are expected to be released soon, which promise to outperform the current short-read technologies in terms of throughput. Despite the flood of data expected from this technology, the data analysis solutions currently available are only designed to manage small projects and are not scalable. Here we present HPG Pore, a toolkit for …

Application of Graph Clustering and Visualisation Methods to Analysis of Biomolecular Data

2018

In this paper we present an approach based on integrated use of graph clustering and visualisation methods for semi-supervised discovery of biologically significant features in biomolecular data sets. We describe several clustering algorithms that have been custom designed for analysis of biomolecular data and feature an iterated two step approach involving initial computation of thresholds and other parameters used in clustering algorithms, which is followed by identification of connected graph components, and, if needed, by adjustment of clustering parameters for processing of individual subgraphs.

EFMviz

2020

Elementary Flux Modes (EFMs) are a tool for constraint-based modeling and metabolic network analysis. However, systematic and automated visualization of EFMs, capable of integrating various data types is still a challenge. In this study, we developed an extension for the widely adopted COBRA Toolbox, EFMviz, for analysis and graphical visualization of EFMs as networks of reactions, metabolites and genes. The analysis workflow offers a platform for EFM visualization to improve EFM interpretability by connecting COBRA toolbox with the network analysis and visualization software Cytoscape. The biological applicability of EFMviz is demonstrated in two use cases on medium (Escherichia coli, iAF1…

Quantitatively characterizing drug-induced arrhythmic contractile motions of human stem cell-derived cardiomyocytes.

2018

Quantification of abnormal contractile motions of cardiac tissue has been a noteworthy challenge and significant limitation in assessing and classifying the drug-induced arrhythmias (i.e. Torsades de pointes). To overcome these challenges, researchers have taken advantage of computational image processing tools to measure contractile motion from cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs). However, the amplitude and frequency analysis of contractile motion waveforms doesn't produce sufficient information to objectively classify the degree of variations between two or more sets of cardiac contractile motions. In this paper, we generated contractile motion dat…

Data mining approaches to identify biomineralization related sequences.

2015

Proteomics is an efficient high throughput technique developed to identify proteins from a crude extract using sequence homology. Advances in Next Generation Sequencing (NGS) have led to increase knowledge of several non-model species. In the field of calcium carbonate biomineralization, the paucity of available sequences (such as the ones of mollusc shells) is still a bottleneck in most proteomic studies. Indeed, this technique needs proteins databases to find homology. The aim of this study was to perform different data mining approaches in order to identify novel shell proteins. To this end, we disposed of several publicly non-model molluscs databases. Previously identified molluscan she…

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…