Search results for " PREDICTION"
showing 10 items of 366 documents
Extracting similar sub-graphs across PPI Networks
2009
Singling out conserved modules (corresponding to connected sub-graphs) throughout protein-protein interaction networks of different organisms is a main issue in bioinformatics because of its potential applications in biology. This paper presents a method to discover highly matching sub-graphs in such networks. Sub-graph extraction is carried out by taking into account, on the one side, both protein sequence and network structure similarities and, on the other side, both quantitative and reliability information possibly available about interactions. The method is conceived as a generalization of a known technique, able to discover functional orthologs in interaction networks. Some preliminar…
A computer system to perform structure comparison using TOPS representations of protein structure
2001
We describe the design and implementation of a fast topology-based method for protein structure comparison. The approach uses the TOPS topological representation of protein structure, aligning two structures using a common discovered pattern and generating measure of distance derived from an insert score. Heavy use is made of a constraint-based pattern-matching algorithm for TOPS diagrams that we have designed and described elsewhere (Bioinformatics 15(4) (1999) 317). The comparison system is maintained at the European Bioinformatics Institute and is available over the Web at tops.ebi.ac.uk/tops. Users submit a structure description in Protein Data Bank (PDB) format and can compare it with …
Experimental Evaluation of Protein Secondary Structure Predictors
2009
Understanding protein biological function is a key issue in modern biology, which is largely determined by its 3D shape. Protein 3D shape, in its turn, is functionally implied by its amino acid sequence. Since the direct inspection of such 3D structures is rather expensive and time consuming, a number of software techniques have been developed in the last few years that predict a spatial model, either of the secondary or of the tertiary form, for a given target protein starting from its amino acid sequence. This paper offers a comparison of several available automatic secondary structure prediction tools. The comparison is of the experimental kind, where two relevant sets of proteins, a non…
Protein Structure Metapredictors
2013
Using Deep Learning to Extrapolate Protein Expression Measurements
2020
Mass spectrometry (MS)-based quantitative proteomics experiments typically assay a subset of up to 60% of the ≈20 000 human protein coding genes. Computational methods for imputing the missing values using RNA expression data usually allow only for imputations of proteins measured in at least some of the samples. In silico methods for comprehensively estimating abundances across all proteins are still missing. Here, a novel method is proposed using deep learning to extrapolate the observed protein expression values in label-free MS experiments to all proteins, leveraging gene functional annotations and RNA measurements as key predictive attributes. This method is tested on four datasets, in…
Prognostic Value of Troponins in Patients With or Without Coronary Heart Disease: Is it Dependent on Structure and Biology?
2020
Convincing evidence has emerged that cardiac troponins (cTns) T and I are the biochemical gold standard for diagnosing cardiac injury, and may also be used as efficient screening and risk stratification tools, especially when measured with the new high-sensitivity (hs-) immunoassays. In this narrative review, we aim to explore and critically discuss the results of recent epidemiological studies that have attempted to characterise the prognostic value of cTns in patients with or without cardiovascular disease, and then interpret this information according to cTn biology. Overall, all recent studies agree that higher blood levels of cTns reflect the larger risk of cardiovascular events and/or…
New set of 2D/3D thermodynamic indices for proteins. A formalism based on "Molten Globule" theory
2010
Abstract We define eight new macromolecular indices, and several related descriptors for proteins. The coarse grained methodology used for its deduction ensures its fast execution and becomes a powerful potential tool to explore large databases of protein structures. The indices are intended for stability studies, predicting Φ -values, predicting folding rate constants, protein QSAR/QSPR as well as protein alignment studies. Also, these indices could be used as scoring function in protein-protein docking or 3D protein structure prediction algorithms and any others applications which need a numerical code for proteins and/or residues from 2D or 3D format.
Search for the Associated Production of the Standard-Model Higgs Boson in the All-Hadronic Channel
2009
We report on a search for the standard-model Higgs boson in pp collisions at s=1.96 TeV using an integrated luminosity of 2.0 fb(-1). We look for production of the Higgs boson decaying to a pair of bottom quarks in association with a vector boson V (W or Z) decaying to quarks, resulting in a four-jet final state. Two of the jets are required to have secondary vertices consistent with B-hadron decays. We set the first 95% confidence level upper limit on the VH production cross section with V(-> qq/qq('))H(-> bb) decay for Higgs boson masses of 100-150 GeV/c(2) using data from run II at the Fermilab Tevatron. For m(H)=120 GeV/c(2), we exclude cross sections larger than 38 times the standard-m…
THERP and HEART integrated methodology for human error assessment
2015
Abstract THERP and HEART integrated methodology is proposed to investigate accident scenarios that involve operator errors during high-dose-rate (HDR) treatments. The new approach has been modified on the basis of fuzzy set concept with the aim of prioritizing an exhaustive list of erroneous tasks that can lead to patient radiological overexposures. The results allow for the identification of human errors that are necessary to achieve a better understanding of health hazards in the radiotherapy treatment process, so that it can be properly monitored and appropriately managed.
The upgraded ISOLDE yield database – A new tool to predict beam intensities
2020
At the CERN-ISOLDE facility a variety of radioactive ion beams are available to users of the facility. The number of extractable isotopes estimated from yield database data exceeds 1000 and is still increasing. Due to high demand and scarcity of available beam time, precise experiment planning is required. The yield database stores information about radioactive beam yields and the combination of target material and ion source needed to extract a certain beam along with their respective operating conditions. It allows to investigate the feasibility of an experiment and the estimation of required beamtime. With the increasing demand for ever more exotic beams, needs arise to extend the functi…