Search results for "Data"
showing 10 items of 12992 documents
Enabling openness of valuable information resources: Curbing data subtractability and exclusion
2019
In this paper we investigate how data openness can be made possible in communal settings. We adopt a utility perspective that foregrounds the use value of data, conceptualizing them as “goods.” On the basis of this conceptualization we explore 2 key goods' attributes: subtractability and exclusion. Our theoretical basis is built upon concepts from the theory of the commons, power theorizing, and notions related to data and information. Empirically, we investigate openness in the genetics domain through a longitudinal study of the evolving communal infrastructure for data related to 2 genes influencing women's susceptibility to breast and ovarian cancer (BRCA1 and BRCA2). We follow the conti…
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 …
Deep learning architectures for prediction of nucleosome positioning from sequences data
2018
Abstract Background Nucleosomes are DNA-histone complex, each wrapping about 150 pairs of double-stranded DNA. Their function is fundamental for one of the primary functions of Chromatin i.e. packing the DNA into the nucleus of the Eukaryote cells. Several biological studies have shown that the nucleosome positioning influences the regulation of cell type-specific gene activities. Moreover, computational studies have shown evidence of sequence specificity concerning the DNA fragment wrapped into nucleosomes, clearly underlined by the organization of particular DNA substrings. As the main consequence, the identification of nucleosomes on a genomic scale has been successfully performed by com…
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.
Next-generation sequencing: big data meets high performance computing
2017
The progress of next-generation sequencing has a major impact on medical and genomic research. This high-throughput technology can now produce billions of short DNA or RNA fragments in excess of a few terabytes of data in a single run. This leads to massive datasets used by a wide range of applications including personalized cancer treatment and precision medicine. In addition to the hugely increased throughput, the cost of using high-throughput technologies has been dramatically decreasing. A low sequencing cost of around US$1000 per genome has now rendered large population-scale projects feasible. However, to make effective use of the produced data, the design of big data algorithms and t…
Network Analysis: Ten Years Shining Light on Host–Parasite Interactions
2020
Biological interactions are key drivers of ecological and evolutionary processes. The complexity of such interactions hinders our understanding of ecological systems and our ability to make effective predictions in changing environments. However, network analysis allows us to better tackle the complexity of ecosystems because it extracts the properties of an ecological system according to the number and distribution of links among interacting entities. The number of studies using network analysis to solve ecological and evolutionary questions in parasitology has increased over the past decade. Here, we synthesise the contribution of network analysis toward disentangling host-parasite proces…
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…
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…