Search results for "computing"
showing 10 items of 25279 documents
Erratum
2016
Author(s): Klionsky, DJ; Abdelmohsen, K; Abe, A; Abedin, MJ; Abeliovich, H; Arozena, AA; Adachi, H; Adams, CM; Adams, PD; Adeli, K; Adhihetty, PJ; Adler, SG; Agam, G; Agarwal, R; Aghi, MK; Agnello, M; Agostinis, P; Aguilar, PV; Aguirre-Ghiso, J; Airoldi, EM; Ait-Si-Ali, S; Akematsu, T; Akporiaye, ET; Al-Rubeai, M; Albaiceta, GM; Albanese, C; Albani, D; Albert, ML; Aldudo, J; Algul, H; Alirezaei, M; Alloza, I; Almasan, A; Almonte-Beceril, M; Alnemri, ES; Alonso, C; Altan-Bonnet, N; Altieri, DC; Alvarez, S; Alvarez-Erviti, L; Alves, S; Amadoro, G; Amano, A; Amantini, C; Ambrosio, S; Amelio, I; Amer, AO; Amessou, M; Amon, A; An, Z; Anania, FA; Andersen, SU; Andley, UP; Andreadi, CK; Andrieu-Ab…
Discovering discriminative graph patterns from gene expression data
2016
We consider the problem of mining gene expression data in order to single out interesting features characterizing healthy/unhealthy samples of an input dataset. We present an 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. Our main goal is that of singling out interesting differences between healthy and unhealthy samples, through the extraction of "discriminative patterns" among graphs belonging to the two different sample sets. Differently from the other…
Impact of poplar-based phytomanagement on soil properties and microbial communities in a metal-contaminated site
2016
Despite a long history of use in phytomanagement strategies, the impacts of poplar trees on the structure and function of microbial communities that live in the soil remain largely unknown. The current study combined fungal and bacterial community analyses from different management regimes using Illumina-based sequencing with soil analysis. The poplar phytomanagement regimes led to a significant increase in soil fertility and a decreased bioavailability of Zn and Cd, in concert with changes in the microbial communities. The most notable changes in the relative abundance of taxa and operational taxonomic units unsurprisingly indicated that root and soil constitute distinct ecological microbi…
parSRA: A framework for the parallel execution of short read aligners on compute clusters
2018
The growth of next generation sequencing datasets poses as a challenge to the alignment of reads to reference genomes in terms of both accuracy and speed. In this work we present parSRA, a parallel framework to accelerate the execution of existing short read aligners on distributed-memory systems. parSRA can be used to parallelize a variety of short read alignment tools installed in the system without any modification to their source code. We show that our framework provides good scalability on a compute cluster for accelerating the popular BWA-MEM and Bowtie2 aligners. On average, it is able to accelerate sequence alignments on 16 64-core nodes (in total, 1024 cores) with speedup of 10.48 …
Imaging through scattering media by microstructured illumination
2016
We describe a method to image objects through scattering media based on microstructured illumination. A spatial light modulator is used to project a set of microstructured light patterns onto the sample. The image is retrieved computationally from the photocurrent fluctuations provided by a detector with no spatial structure. We review several optical setups developed in the last years with different illumination strategies and applied to different turbid media. In particular we introduce a new non-invasive optical system based on a reflection configuration. Our technique does not require coherent light, raster scanning, time-gated detection or a-priori calibration processes. Furthermore it…
CUDA-enabled hierarchical ward clustering of protein structures based on the nearest neighbour chain algorithm
2015
Clustering of molecular systems according to their three-dimensional structure is an important step in many bioinformatics workflows. In applications such as docking or structure prediction, many algorithms initially generate large numbers of candidate poses (or decoys), which are then clustered to allow for subsequent computationally expensive evaluations of reasonable representatives. Since the number of such candidates can easily range from thousands to millions, performing the clustering on standard central processing units (CPUs) is highly time consuming. In this paper, we analyse and evaluate different approaches to parallelize the nearest neighbour chain algorithm to perform hierarc…
Partitioned learning of deep Boltzmann machines for SNP data.
2016
Abstract Motivation Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. Results After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen…
ParDRe: faster parallel duplicated reads removal tool for sequencing studies
2016
This is a pre-copyedited, author-produced version of an article accepted for publication in Bioinformatics following peer review. The version of record [insert complete citation information here] is available online at: https://doi.org/10.1093/bioinformatics/btw038 [Abstract] Summary: Current next generation sequencing technologies often generate duplicated or near-duplicated reads that (depending on the application scenario) do not provide any interesting biological information but can increase memory requirements and computational time of downstream analysis. In this work we present ParDRe , a de novo parallel tool to remove duplicated and near-duplicated reads through the clustering of S…
Gene-based and semantic structure of the Gene Ontology as a complex network
2012
The last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The information accumulated time-by-time and included in the GO is encoded in the definition of terms and in the setting up of semantic relations amongst terms. This approach might be usefully complemented by a bottom-up approach based on the knowledge of relationships amongst genes. To this end, we investigate the Gene Ontology from a complex network perspective. We consider the semantic network of terms naturally associated with the semantic relationships provided by the Gene Ontology consortium and a gene-based …
panISa: ab initio detection of insertion sequences in bacterial genomes from short read sequence data.
2018
Abstract Motivation The advent of next-generation sequencing has boosted the analysis of bacterial genome evolution. Insertion sequence (IS) elements play a key role in prokaryotic genome organization and evolution, but their repetitions in genomes complicate their detection from short-read data. Results PanISa is a software pipeline that identifies IS insertions ab initio in bacterial genomes from short-read data. It is a highly sensitive and precise tool based on the detection of read-mapping patterns at the insertion site. PanISa performs better than existing IS detection systems as it is based on a database-free approach. We applied it to a high-risk clone lineage of the pathogenic spec…