A computer system to perform structure comparison using TOPS representations of protein structure

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 Gilbert et al. (1999). The comparison system is maintained at the European Bioinformatics Institute and is available over the Web via the at tops.ebi.ac.uk/tops. Users submit a structure description in Protein Data Bank (PDB) format and can compare it with structures in the entire PDB or a representative subset of protein domains, receiving the results by email

Domain discovery method for topological profile searches in protein structures

We describe a method for automated domain discovery for topological profile searches in protein structures. The method is used in a system TOPStructure for fast prediction of CATH classification for protein structures (given as PDB files). It is important for profile searches in multi-domain proteins, for which the profile method by itself tends to perform poorly. We also present an O(C(n)k +nk2) time algorithm for this problem, compared to the O(C(n)k +(nk)2) time used by a trivial algorithm (where n is the length of the structure, k is the number of profiles and C(n) is the time needed to check for a presence of a given motif in a structure of length n). This method has been developed and is currently used for TOPS representations of protein structures and prediction of CATH classification, but may be applied to other graph-based representations of protein or RNA structures and/or other prediction problems. A protein structure prediction system incorporating the domain discovery method is available at http://bioinf.mii.lu.lv/tops/

Pattern matching and pattern discovery algorithms for protein topologies

We describe algorithms for pattern matching and pattern learning in TOPS diagrams (formal descriptions of protein topologies). These problems can be reduced to checking for subgraph isomorphism and finding maximal common subgraphs in a restricted class of ordered graphs. We have developed a subgraph isomorphism algorithm for ordered graphs, which performs well on the given set of data. The maximal common subgraph problem then is solved by repeated subgraph extension and checking for isomorphisms. Despite the apparent inefficiency such approach gives an algorithm with time complexity proportional to the number of graphs in the input set and is still practical on the given set of data. As a result we obtain fast methods which can be used for building a database of protein topological motifs, and for the comparison of a given protein of known secondary structure against a motif database

An optimized TOPS+ comparison method for enhanced TOPS models

This article has been made available through the Brunel Open Access Publishing Fund.Background Although methods based on highly abstract descriptions of protein structures, such as VAST and TOPS, can perform very fast protein structure comparison, the results can lack a high degree of biological significance. Previously we have discussed the basic mechanisms of our novel method for structure comparison based on our TOPS+ model (Topological descriptions of Protein Structures Enhanced with Ligand Information). In this paper we show how these results can be significantly improved using parameter optimization, and we call the resulting optimised TOPS+ method as advanced TOPS+ comparison method i.e. advTOPS+. Results We have developed a TOPS+ string model as an improvement to the TOPS [1-3] graph model by considering loops as secondary structure elements (SSEs) in addition to helices and strands, representing ligands as first class objects, and describing interactions between SSEs, and SSEs and ligands, by incoming and outgoing arcs, annotating SSEs with the interaction direction and type. Benchmarking results of an all-against-all pairwise comparison using a large dataset of 2,620 non-redundant structures from the PDB40 dataset [4] demonstrate the biological significance, in terms of SCOP classification at the superfamily level, of our TOPS+ comparison method. Conclusions Our advanced TOPS+ comparison shows better performance on the PDB40 dataset [4] compared to our basic TOPS+ method, giving 90 percent accuracy for SCOP alpha+beta; a 6 percent increase in accuracy compared to the TOPS and basic TOPS+ methods. It also outperforms the TOPS, basic TOPS+ and SSAP comparison methods on the Chew-Kedem dataset [5], achieving 98 percent accuracy. Software Availability: The TOPS+ comparison server is available at http://balabio.dcs.gla.ac.uk/mallika/WebTOPS/.This article is available through the Brunel Open Access Publishing Fun

Interactive visualisation and exploration of biological data

International audienceno abstrac

The K-trial. A 33-years study of the connections between manuring, soils and crops

In 1958 started a comparative fertilization trial, called the K-trial, within the frames of Scandinavian Research Circle for Biodynamic Agriculture. The trial ended in 1990. This report accounts for the results that have been collected over this 33-year long trial-period. The ambition with the trial was to develop methods of analyses that could indicate foodstuff quality. The long-term trial-period also brought along, a possibility to study the correlation of fertilization, soil and crop. The difference between a cultivation that uses organic fertilizer compared to one that uses mineral fertilizer and where both achieves comparable yield-levels can according to the results from the K-trial be summarized as: Soil - higher enzyme-activity, soil respiration and occurrence of earthworms - more deep going soil processes - considerably higher nitrogen-mineralising capability - better soil-fertility Crop - better storage efficiency and resistance against decomposition - higher grade of maturity - higher amount of leguminous plants in the clover/grass ley The results from the K-trial in this report, has been compared to the results from two ”daughter-trials”. In these trials two different systems was compared, biodynamic agriculture and conventional agriculture. The effects of these different fertilizing-systems on the quality in products in the K-trial corresponded with the results from the daughter-trials. In comparison with the conventional methods, the crude protein content was lower in the organic variants, but the quality in the protein was higher in potatoes and wheat. Resistance against decomposition and storage-quality for potatoes, was higher in the organic variants and the same applied to the starch-quality in wheat. The organic fertilisation resulted in a higher fertility in soil and crops, with higher quality in protein and starch. The differences were more difficult to determine between de variant that was fertilized with compost and the ones that received raw farmyard manure, partly because the compost was also treated with the biodynamic compost-preparations. Somewhat simplified, the differences consisted in the fresh farm-yard manure more strongly did stimulate the vegetative processes and the metabolism in soil and crop, while the compost more strongly contributed to building up the soil structure and the form of the crop. The biodynamic field-preparations effects could be determined as a positive effect on the yield in all crops, except the first harvest of clover/grass ley. The effect of the preparations on yield was largest during the years when yield-level was low. Field-preparation effects were also apparent in the more deep-going soil processes, and in higher amount-amount in the clover/grass ley. This calculated supply of nitrogen by this higher amount of amount plants amounted to approx. 16 kg N per hectare and year. The results from the K-trial indicate the demand of a discussion on issues concerning food-stuff-quality. In this report a few aspects on the concept of quality has been treated. Furthermore, formulated is also a frame of a few possible future research-fields connected to the issue of quality

The use of data-mining for the automatic formation of tactics

This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques