Prediction of cottonseed longevity

The objective of this work was to determine the viability equation constants for cottonseed and to detect the occurrence and depletion of hardseededness. Three seedlots of Brazilian cultivars IAC-19 and IAC-20 were tested, using 12 moisture content levels, ranging from 2.2 to 21.7% and three storage temperatures, 40, 50 and 65 degrees C. Seed moisture content level was reached from the initial value (around 8.8%) either by rehydration, in a closed container, or by drying in desiccators containing silica gel, both at 20 degrees C. Twelve seed subsamples for each moisture content/temperature treatment were sealed in laminated aluminium-foil packets and stored in incubators at those temperatures, until complete survival curves were obtained. Seed equilibrium relative humidity was recorded. Hardseededness was detected at moisture content levels below 6% and its releasing was achieved either naturally, during storage period, or artificially through seed coat removal. The viability equation quantified the response of seed longevity to storage environment well with K-E = 9.240, C-W = 5.190, C-H = 0.03965 and C-Q = 0.000426. The lower limit estimated for application of this equation at 65 degrees C was 3.6% moisture content.

A GIS-based empirical model for vegetation prediction in Lefka Ori, Crete

The aim of the study was to establish and verify a predictive vegetation model for plant community distribution in the alti-Mediterranean zone of the Lefka Ori massif, western Crete. Based on previous work three variables were identified as significant determinants of plant community distribution, namely altitude, slope angle and geomorphic landform. The response of four community types against these variables was tested using classification trees analysis in order to model community type occurrence. V-fold cross-validation plots were used to determine the length of the best fitting tree. The final 9node tree selected, classified correctly 92.5% of the samples. The results were used to provide decision rules for the construction of a spatial model for each community type. The model was implemented within a Geographical Information System (GIS) to predict the distribution of each community type in the study site. The evaluation of the model in the field using an error matrix gave an overall accuracy of 71%. The user's accuracy was higher for the Crepis-Cirsium (100%) and Telephium-Herniaria community type (66.7%) and relatively lower for the Peucedanum-Alyssum and Dianthus-Lomelosia community types (63.2% and 62.5%, respectively). Misclassification and field validation points to the need for improved geomorphological mapping and suggests the presence of transitional communities between existing community types.

Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments

MOTIVATION: The accurate prediction of the quality of 3D models is a key component of successful protein tertiary structure prediction methods. Currently, clustering or consensus based Model Quality Assessment Programs (MQAPs) are the most accurate methods for predicting 3D model quality; however they are often CPU intensive as they carry out multiple structural alignments in order to compare numerous models. In this study, we describe ModFOLDclustQ - a novel MQAP that compares 3D models of proteins without the need for CPU intensive structural alignments by utilising the Q measure for model comparisons. The ModFOLDclustQ method is benchmarked against the top established methods in terms of both accuracy and speed. In addition, the ModFOLDclustQ scores are combined with those from our older ModFOLDclust method to form a new method, ModFOLDclust2, that aims to provide increased prediction accuracy with negligible computational overhead. RESULTS: The ModFOLDclustQ method is competitive with leading clustering based MQAPs for the prediction of global model quality, yet it is up to 150 times faster than the previous version of the ModFOLDclust method at comparing models of small proteins (<60 residues) and over 5 times faster at comparing models of large proteins (>800 residues). Furthermore, a significant improvement in accuracy can be gained over the previous clustering based MQAPs by combining the scores from ModFOLDclustQ and ModFOLDclust to form the new ModFOLDclust2 method, with little impact on the overall time taken for each prediction. AVAILABILITY: The ModFOLDclustQ and ModFOLDclust2 methods are available to download from: http://www.reading.ac.uk/bioinf/downloads/ CONTACT: l.j.mcguffin@reading.ac.uk.

Prediction of global and local model quality in CASP8 using the ModFOLD server

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0-an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/.

Intrinsic disorder prediction from the analysis of multiple protein fold recognition models

Motivation: Intrinsic protein disorder is functionally implicated in numerous biological roles and is, therefore, ubiquitous in proteins from all three kingdoms of life. Determining the disordered regions in proteins presents a challenge for experimental methods and so recently there has been much focus on the development of improved predictive methods. In this article, a novel technique for disorder prediction, called DISOclust, is described, which is based on the analysis of multiple protein fold recognition models. The DISOclust method is rigorously benchmarked against the top.ve methods from the CASP7 experiment. In addition, the optimal consensus of the tested methods is determined and the added value from each method is quantified. Results: The DISOclust method is shown to add the most value to a simple consensus of methods, even in the absence of target sequence homology to known structures. A simple consensus of methods that includes DISOclust can significantly outperform all of the previous individual methods tested.

Constrained models of evolution lead to improved prediction of functional linkage from correlated gain and loss of genes

Motivation: We compare phylogenetic approaches for inferring functional gene links. The approaches detect independent instances of the correlated gain and loss of pairs of genes from species' genomes. We investigate the effect on results of basing evidence of correlations on two phylogenetic approaches, Dollo parsminony and maximum likelihood (ML). We further examine the effect of constraining the ML model by fixing the rate of gene gain at a low value, rather than estimating it from the data. Results: We detect correlated evolution among a test set of pairs of yeast (Saccharomyces cerevisiae) genes, with a case study of 21 eukaryotic genomes and test data derived from known yeast protein complexes. If the rate at which genes are gained is constrained to be low, ML achieves by far the best results at detecting known functional links. The model then has fewer parameters but it is more realistic by preventing genes from being gained more than once. Availability: BayesTraits by M. Pagel and A. Meade, and a script to configure and repeatedly launch it by D. Barker and M. Pagel, are available at http://www.evolution.reading.ac.uk .

Retention time prediction and protein identification

Proteins are commonly identified through enzymatic digestion and generation of short sequence tags or fingerprints of peptide masses by mass spectrometry. Separation methods, such as liquid chromatography and electrophoresis, are often used to fractionate complex protein or peptide mixtures and these separations also provide information on the different species, such as molecular weight and isoelectric point from electrophoresis and hydrophobicity in reversed-phase chromatography. These are also properties that can be predicted from amino acid sequences derived from genomic sequences and used in protein identification. This chapter reviews recently introduced methods based on retention time prediction to extract information from chromatographic separations and the applications to protein identification in organisms with small and large genomes. Novel data on retention time prediction of posttranslationally modified peptides is also presented.

Accessing biodiversity resources in computational environments from workflow applications

In the Biodiversity World (BDW) project we have created a flexible and extensible Web Services-based Grid environment for biodiversity researchers to solve problems in biodiversity and analyse biodiversity patterns. In this environment, heterogeneous and globally distributed biodiversity-related resources such as data sets and analytical tools are made available to be accessed and assembled by users into workflows to perform complex scientific experiments. One such experiment is bioclimatic modelling of the geographical distribution of individual species using climate variables in order to predict past and future climate-related changes in species distribution. Data sources and analytical tools required for such analysis of species distribution are widely dispersed, available on heterogeneous platforms, present data in different formats and lack interoperability. The BDW system brings all these disparate units together so that the user can combine tools with little thought as to their availability, data formats and interoperability. The current Web Servicesbased Grid environment enables execution of the BDW workflow tasks in remote nodes but with a limited scope. The next step in the evolution of the BDW architecture is to enable workflow tasks to utilise computational resources available within and outside the BDW domain. We describe the present BDW architecture and its transition to a new framework which provides a distributed computational environment for mapping and executing workflows in addition to bringing together heterogeneous resources and analytical tools.

Predicting functional gene links from phylogenetic-statistical analyses of whole genomes

An important element of the developing field of proteomics is to understand protein-protein interactions and other functional links amongst genes. Across-species correlation methods for detecting functional links work on the premise that functionally linked proteins will tend to show a common pattern of presence and absence across a range of genomes. We describe a maximum likelihood statistical model for predicting functional gene linkages. The method detects independent instances of the correlated gain or loss of pairs of proteins on phylogenetic trees, reducing the high rates of false positives observed in conventional across-species methods that do not explicitly incorporate a phylogeny. We show, in a dataset of 10,551 protein pairs, that the phylogenetic method improves by up to 35% on across-species analyses at identifying known functionally linked proteins. The method shows that protein pairs with at least two to three correlated events of gain or loss are almost certainly functionally linked. Contingent evolution, in which one gene's presence or absence depends upon the presence of another, can also be detected phylogenetically, and may identify genes whose functional significance depends upon its interaction with other genes. Incorporating phylogenetic information improves the prediction of functional linkages. The improvement derives from having a lower rate of false positives and from detecting trends that across-species analyses miss. Phylogenetic methods can easily be incorporated into the screening of large-scale bioinformatics datasets to identify sets of protein links and to characterise gene networks.

The measurement of maternal plasma corticotropin-releasing factor (CRF) and CRF-binding protein improves the early prediction of preeclampsia

In the present study we measured maternal plasma concentrations of two placental neurohormones, corticotropin-releasing factor (CRF) and CRF-binding protein (CRF-BP), in 58 at-risk pregnant women consecutively enrolled between 28 and 29 wk of pregnancy to evaluate whether their evaluation may predict third trimester-onset preeclampsia ( PE). The statistical significance was assessed by t test. The cut-off points for defining altered CRF and CRF-BP levels for prediction of PE were chosen by receiving operator characteristics curve analysis, and the probability of developing PE was calculated for several combinations of hormone testing results. CRF and CRF-BP levels were significantly ( both P < 0.0001) higher and lower, respectively, in the patients (n = 20) who later developed PE than in those who did not present PE at follow-up. CRF at the cut-off 425.95 pmol/liter achieved a sensitivity of 94.8% and a specificity of 96.9%, whereas CRF-BP at the cut-off 125.8 nmol/liter combined a sensitivity of 92.5% and a specificity of 82.5% as single markers for prediction of PE. The probability of PE was 34.5% in the whole study population, 93.75% when both CRF and CRF-BP levels were changed, and 0% if both hormone markers were unaltered. The measurement of CRF and CRF-BP levels may add significant prognostic information for predicting PE in at-risk pregnant women.

Design, synthesis and computational modelling of aromatic tweezer-molecules as models for chain-folding polymer blends

Novel 'tweezer-type' complexes that exploit the interactions between pi-electron-rich pyrenyl groups and pi-electron deficient diimide units have been designed and synthesised. The component molecules leading to complex formation were accessed readily from commercially available starting materials through short and efficient syntheses. Analysis of the resulting complexes, using the visible charge-transfer band, revealed association constants that increased sequentially from 130 to 11,000 M-1 as increasing numbers of pi-pi-stacking interactions were introduced into the systems. Computational modelling was used to analyse the structures of these complexes, revealing low-energy chain-folded conformations for both components, which readily allow close, multiple pi-pi-stacking and hydrogen bonding to be achieved. In this paper, we give details of our initial studies of these complexes and outline how their behaviour could provide a basis for designing self-healing polymer blends for use in adaptive coating systems. (C) 2008 Elsevier Ltd. All rights reserved.

Geometrical isomers of [TEAH][Co(L-Se)(2)]center dot xH(2)O: synthesis, structural, spectroscopic and computational studies

Trans-1, [HNEt3][Co-III(L-Se)(2)]center dot H2O and cis-1, [HNEt3][Co-III(L-Se)(2)]center dot 3H(2)O have been synthesized and characterized by single-crystal X-ray studies. The counter ion Et3NH+ plays a crucial role in the crystal packing leading to the formation of two distinctly different supramolecular assemblies in the two complexes. In trans-1, Co-bisphenolate units and triethylamine molecules are arranged in a linear fashion leading to a supramolecular columnar assembly along the crystallographic a-axis. In this assembly, triethylammonium ions are sandwiched between successive Co-bisphenolate units and act as gluing agents joining Co-bisphenolate units on either side through C-H center dot center dot center dot pi interactions. In sharp contrast to trans-1, Co-bisphenolate units and triethylammonium ions in cis-1 are arranged in a helical supramolecular assembly through similar C-H center dot center dot center dot pi interactions along the crystallographic b-axis. The Se center dot center dot center dot Se van der Waals interactions may be responsible for the predominant occurrence of the cis-isomer. The cyclic voltammetric studies showed quasi-reversible waves for the cobalt(III) -> cobalt(II) reductions with E-1/2 = 0.635 and 0.628 V vs. Ag/AgCl for cis-1 (at similar to 5 degrees C) and trans-1 (at similar to 25 degrees C), respectively. DFT calculations show that the trans-form is the thermodynamic product with higher stability than the cis-one, which is consistent with the variable temperature H-1 NMR studies

Ab initio prediction of the infrared-absorption spectrum of the C2Cl radical

The three lowest (1(2)A('), 2(2)A('), and 1(2)A(')) potential-energy surfaces of the C2Cl radical, correlating at linear geometries with (2)Sigma(+) and (2)Pi states, have been studied ab initio using a large basis set and multireference configuration-interaction techniques. The electronic ground state is confirmed to be bent with a very low barrier to linearity, due to the strong nonadiabatic electronic interactions taking place in this system. The rovibronic energy levels of the (CCCl)-C-12-C-12-Cl-35 isotopomer and the absolute absorption intensities at a temperature of 5 K have been calculated, to an upper limit of 2000 cm(-1), using diabatic potential-energy and dipole moment surfaces and a recently developed variational method. The resulting vibronic states arise from a strong mixture of all the three electronic components and their assignments are intrinsically ambiguous. (c) 2005 American Institute of Physics.

Ab initio prediction of the infrared absorption spectrum of the C2Br radical

The first three electronic states (1(2)A', 2(2)A', 1(2)A '') of the C2Br radical, correlating at linear geometries with (2)Sigma(+) and (2)Pi states, have been studied ab initio, using Multi Reference Configuration Interaction techniques. The electronic ground state is found to have a bent equilibrium geometry, R-CC = 1.2621 angstrom, R-CBr = 1.7967 angstrom, < CCBr 156.1 degrees, with a very low barrier to linearity. Similarly to the valence isoelectronic radicals C2F and C2Cl, this anomalous behaviour is attributed to a strong three-state non-adiabatic electronic interaction. The Sigma, Pi(1/2), Pi(3/2) vibronic energy levels and their absolute infrared absorption intensities at a temperature of 5K have been calculated for the (CCBr)-C-12-C-12-Br-79 isotopomer, to an upper limit of 2000 cm(-1), using ab initio diabatic potential energy and dipole moment surfaces and a recently developed variational method.