1,720,992 research outputs found
ExpEdit: a webserver to explore human RNA editing in RNA-Seq experiments
No full textExpEdit is a web application for assessing RNA editing in human at known or user-specified sites supported by transcript data obtained by RNA-Seq experiments. Mapping data (in SAM/BAM format) or directly sequence reads [in FASTQ/short read archive (SRA) format] can be provided as input to carry out a comparative analysis against a large collection of known editing sites collected in DARNED database as well as other user-provided potentially edited positions. Results are shown as dynamic tables containing University of California, Santa Cruz (UCSC) links for a quick examination of the genomic context
Optical properties of Cr3+-ions in LaSr2Ga11O20
No full textThe optical properties of Cr3+ ions in the disordered LaSr2Ga11O20 crystal have been investigated through absorption, emission, excitation spectra. Polarized excitation measurements allows us to evaluate the crystal field parameters and to infer the distortion of the octahedral site of Cr3+. In spite of the relatively low value of the crystal field (Dq/B = 2.26) obtained from optical data, the emission spectra are constituted by two narrow lines. This behavior, typical of strong field material, is explained by an even lower value of the crystal field corresponding to the 2E, 4T2 crossing point obtained by means of the Tanabe-Sugano diagram. The value of the splitting and the width of the emission lines, intermediate between crystals and glasses, confirm the disordered structure of this crystal
Empowering precision medicine through high performance computing clusters
Full text linkThe role of High Performance Computing (HPC) in Medicine is greatly increase in these last years,
moving from basic research to the clinics. With the advent of Next Generation Sequencing (NGS)
technologies, diverse areas of human health have been investigated through different omics
techniques. The extensive use of these NGS platforms to high throughput profile human health
issues in a cost-efficient manner, is generating huge amount of sequencing data pushing
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bioinformatic research in the big-data field. Speed, accuracy and reproducibility of massively
sequencing analysis have allowed to transfer molecular biology knowledge into precision medicine.
Furthermore, Molecular Dynamics (MD) earned a great importance in aiding genome research.
Sequencing studies of cancer have allowed to detect and characterize mutated genes that drive
tumorigenesis. As a complementary approach, from a biophysical perspective, MD simulations,
executed on HPC architectures, have permitted to investigate the role played by pathological
mutations on the molecular mechanism of activation
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
CSTminer: a web tool for the identification of coding and noncoding conserved sequence tags through cross-species genome comparison
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A study of nucleotide occurrence distributions in DNA coding segments
No full textIn this paper we present a general strategy designed to study the occurrence frequency distributions of oligonucleotides in DNA coding segments and to deal with the problem of detecting possible patterns of genomic compositional inhomogeneities and disuniformities. Identifying specific tendencies or peculiar deviations in the distributions of the effective occurrence frequencies of oligonucleotides, with respect to what can be a priori expected, is of the greatest importance in biology. Differences between expected and actual distributions may in fact suggest or confirm the existence of specific biological mechanisms related to them. Similarly, a marked deviation in the occurrence frequency of an oligonucleotide may suggest that it belongs to the class of so-called "DNA signal (target) sequences". The approach we have elaborated is innovative in various aspects. Firstly, the analysis of the genomic data is carried out in the light of the observation that the distribution of the four nucleotides along the coding regions of the genoma is biased by the existence of a well-defined "reading frame". Secondly, the "experimental" numbers found by counting the occurrences of the various oligonucleotide sequences are appropriately corrected for the many kinds of mistakes and redundancies present in the available genetic Data Bases. A methodologically significant further improvement of our approach over the existing searching strategies is represented by the fact that, in order to decide whether or not the (corrected) "experimental" value of the occurrence frequency of a given oligonucleotide is within statistical expectations, a measure of the strength of the selective pressure, having acted on it in the course of the evolution, is assigned to the sequence, in a way that takes into account both the value of the "experimental" occurrence frequency of the sequence and the magnitude of the probability that this number might be the result of statistical fluctuations. If the strength of the selective pressure evaluated in this fashion turns out to be sufficiently large, the corresponding sequence will be considered to have an occurrence frequency beyond expectations and, hence, to be statistically and biologically interesting
ODESSA: A high performance analysis pipeline for Ultra Deep targeted Exome Sequencing data
No full textThe last decade has seen the development of a variety of so-called 'next-generation' sequencing (NGS) technologies, that have revolutionized the field of genomics and post-genomics. In cancer research area, as NGS permeates the cancer biomarker realm and cost of NGS declines, hospitals and clinics will deploy deep sequencing as a means to personalize cancer diagnostics and therapeutics. Here we provide a new automated high-performance bioinformatics web platform, ODESSA (Online Deep Exome Sequencing Software Analysis), developed for targeting genes at high coverage through deep sequencing with the maximum usability, and focused on rational diagnosis of targeted therapies
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