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PubMed2002

Simplifying amino acid alphabets by means of a branch and bound algorithm and substitution matrices.

MOTIVATION: Protein and DNA are generally represented by sequences of letters. In a number of circumstances simplified alphabets (where one or more letters would be represented by the same symbol) have proved their potential utility in several fields of bioinformatics including searching for patterns occurring at an unexpected rate, studying protein folding and finding consensus sequences in multiple alignments. The main issue addressed in this paper is the possibility of finding a general approach that would allow an exhaustive analysis of all the possible simplified alphabets, using substitution matrices like PAM and BLOSUM as a measure for scoring. RESULTS: The computational approach presented in this paper has led to a computer program called AlphaSimp (Alphabet Simplifier) that can perform an exhaustive analysis of the possible simplified amino acid alphabets, using a branch and bound algorithm together with standard or user-defined substitution matrices. The program returns a ranked list of the highest-scoring simplified alphabets. When the extent of the simplification is limited and the simplified alphabets are maintained above ten symbols the program is able to complete the analysis in minutes or even seconds on a personal computer. However, the performance becomes worse, taking up to several hours, for highly simplified alphabets. AVAILABILITY: AlphaSimp and other accessory programs are available at http://bioinformatics.cribi.unipd.it/alphasimp

Algorithms↗
PubMed1998

Combined multiple sequence reduced protein model approach to predict the tertiary structure of small proteins.

By incorporating predicted secondary and tertiary restraints into ab initio folding simulations, low resolution tertiary structures of a test set of 20 nonhomologous proteins have been predicted. These proteins, which represent all secondary structural classes, contain from 37 to 100 residues. Secondary structural restraints are provided by the PHD secondary structure prediction algorithm that incorporates multiple sequence information. Predicted tertiary restraints are obtained from multiple sequence alignments via a two-step process: First, "seed" side chain contacts are identified from a correlated mutation analysis, and then, the seed contacts are "expanded" by an inverse folding algorithm. These predicted restraints are then incorporated into a lattice based, reduced protein model. Depending upon fold complexity, the resulting nativelike topologies exhibit a coordinate root-mean-square deviation, cRMSD, from native between 3.1 and 6.7 A. Overall, this study suggests that the use of restraints derived from multiple sequence alignments combined with a fold assembly algorithm is a promising approach to the prediction of the global topology of small proteins.

Algorithms↗
PubMed2002

Of truth and pathways: chasing bits of information through myriads of articles.

Knowledge on interactions between molecules in living cells is indispensable for theoretical analysis and practical applications in modern genomics and molecular biology. Building such networks relies on the assumption that the correct molecular interactions are known or can be identified by reading a few research articles. However, this assumption does not necessarily hold, as truth is rather an emerging property based on many potentially conflicting facts. This paper explores the processes of knowledge generation and publishing in the molecular biology literature using modelling and analysis of real molecular interaction data. The data analysed in this article were automatically extracted from 50000 research articles in molecular biology using a computer system called GeneWays containing a natural language processing module. The paper indicates that truthfulness of statements is associated in the minds of scientists with the relative importance (connectedness) of substances under study, revealing a potential selection bias in the reporting of research results. Aiming at understanding the statistical properties of the life cycle of biological facts reported in research articles, we formulate a stochastic model describing generation and propagation of knowledge about molecular interactions through scientific publications. We hope that in the future such a model can be useful for automatically producing consensus views of molecular interaction data.

Algorithms↗
PubMed2005

Conservative extraction of over-represented extensible motifs.

MOTIVATION: The discovery of motifs in biosequences is frequently torn between the rigidity of the model on the one hand and the abundance of candidates on the other. In particular, the variety of motifs described by strings that include 'don't care' (dot) patterns escalates exponentially with the length of the motif, and this gets only worse if a dot is allowed to stretch up to some prescribed maximum length. This circumstance tends to generate daunting computational burdens, and often gives rise to tables that are impossible to visualize and digest. This is unfortunate, as it seems to preclude precisely those massive analyses that have become conceivable with the increasing availability of massive genomic and protein data. Although a part of the problem is endemic, another part of it seems rooted in the various characterizations offered for the notion of a motif, that are typically based either on syntax or on statistics alone. It seems worthwhile to consider alternatives that result from a prudent combination of these two aspects in the model. RESULTS: We introduce and study a notion of extensible motif in a sequence which tightly combines the structure of the motif pattern, as described by its syntactic specification, with the statistical measure of its occurrence count. We show that a combination of appropriate saturation conditions (expressed in terms of minimum number of dots compatible with a given list of occurrences) and the monotonicity of probabilistic scores over regions of constant frequency afford us significant parsimony in the generation and testing of candidate over-represented motifs. The merits of the method are documented by the results obtained in implementation, which specifically targeted protein sequence families. In all cases tested, the motif reported in PROSITE as the most important in terms of functional/structural relevance emerges among the top 30 extensible motifs returned by our algorithm, often right at the top. Of equal importance seems the fact that the sets of all surprising motifs returned in each experiment are extracted faster and come in much more manageable sizes than would be obtained in the absence of saturation constrains. AVAILABILITY: This software will be available for use with the suite of tools at www.research.ibm.com/bioinformatics.

Algorithms↗
PubMed1999

One sequence, four folds: transitions between an ensemble of metastable folds for the N-terminal domain of CD2.

Recombinant forms of the N-terminal domain of the cell adhesion receptor CD2 adopt a variety of olds by exchange of beta-sheets between adjacent polypeptide chains. Although these interdigitated forms are normally metastable, we have used site-directed mutagenesis to alter the kinetics of formation and relative stabilities of these states, leading to spontaneous formation of monomeric, dimeric, trimeric and tetrameric intertwined folded states. A characteristic feature of these fold-disorder-alternative fold transitions is the independence of each domain folding event, as deduced from kinetic analysis of folding data. Structures for fully interdigitated trimeric and tetrameric forms have been modelled, consistent with both the crystallographic and kinetic data. Although the biological role of these alternative folded states remains unclear, these structures form a remarkable demonstration of the fluidity of structure generated from a single polypeptide chain.

Amino Acid Sequence↗
PubMed2006

Deriving pathway maps from automated text analysis using a grammar-based approach.

We demonstrate how automated text analysis can be used to support the large-scale analysis of metabolic and regulatory pathways by deriving pathway maps from textual descriptions found in the scientific literature. The main assumption is that correct syntactic analysis combined with domain-specific heuristics provides a good basis for relation extraction. Our method uses an algorithm that searches through the syntactic trees produced by a parser based on a Referent Grammar formalism, identifies relations mentioned in the sentence, and classifies them with respect to their semantic class and epistemic status (facts, counterfactuals, hypotheses). The semantic categories used in the classification are based on the relation set used in KEGG (Kyoto Encyclopedia of Genes and Genomes), so that pathway maps using KEGG notation can be automatically generated. We present the current version of the relation extraction algorithm and an evaluation based on a corpus of abstracts obtained from PubMed. The results indicate that the method is able to combine a reasonable coverage with high accuracy. We found that 61% of all sentences were parsed, and 97% of the parse trees were judged to be correct. The extraction algorithm was tested on a sample of 300 parse trees and was found to produce correct extractions in 90.5% of the cases.

Abstracting and Indexing↗
PubMed1982

[Transcapillary fluid exchanges. A program in Basic].

Transcapillary fluid exchanges are analysed with the Wiederhielm's model programmed in this study in Basic language. The physiological variable which are taken in account are: arterial and venous capillary pressures, interstitial pressure and the colloid osmotic pressure of plasma and tissue proteins. This model shows the relationship between filtration, reabsorption, plasma leakage and the lymph flow. Edema resulting from venous and lymphatic obstruction or from a decrease in plasma oncotic pressure are simulated.

Blood Pressure↗
PubMed2005

MBEToolbox: a MATLAB toolbox for sequence data analysis in molecular biology and evolution.

BACKGROUND: MATLAB is a high-performance language for technical computing, integrating computation, visualization, and programming in an easy-to-use environment. It has been widely used in many areas, such as mathematics and computation, algorithm development, data acquisition, modeling, simulation, and scientific and engineering graphics. However, few functions are freely available in MATLAB to perform the sequence data analyses specifically required for molecular biology and evolution. RESULTS: We have developed a MATLAB toolbox, called MBEToolbox, aimed at filling this gap by offering efficient implementations of the most needed functions in molecular biology and evolution. It can be used to manipulate aligned sequences, calculate evolutionary distances, estimate synonymous and nonsynonymous substitution rates, and infer phylogenetic trees. Moreover, it provides an extensible, functional framework for users with more specialized requirements to explore and analyze aligned nucleotide or protein sequences from an evolutionary perspective. The full functions in the toolbox are accessible through the command-line for seasoned MATLAB users. A graphical user interface, that may be especially useful for non-specialist end users, is also provided. CONCLUSION: MBEToolbox is a useful tool that can aid in the exploration, interpretation and visualization of data in molecular biology and evolution. The software is publicly available at http://web.hku.hk/~jamescai/mbetoolbox/ and http://bioinformatics.org/project/?group_id=454

Algorithms↗
PubMed2006

Towards an integrated protein-protein interaction network: a relational Markov network approach.

Protein-protein interactions play a major role in most cellular processes. Thus, the challenge of identifying the full repertoire of interacting proteins in the cell is of great importance and has been addressed both experimentally and computationally. Today, large scale experimental studies of protein interactions, while partial and noisy, allow us to characterize properties of interacting proteins and develop predictive algorithms. Most existing algorithms, however, ignore possible dependencies between interacting pairs and predict them independently of one another. In this study, we present a computational approach that overcomes this drawback by predicting protein-protein interactions simultaneously. In addition, our approach allows us to integrate various protein attributes and explicitly account for uncertainty of assay measurements. Using the language of relational Markov networks, we build a unified probabilistic model that includes all of these elements. We show how we can learn our model properties and then use it to predict all unobserved interactions simultaneously. Our results show that by modeling dependencies between interactions, as well as by taking into account protein attributes and measurement noise, we achieve a more accurate description of the protein interaction network. Furthermore, our approach allows us to gain new insights into the properties of interacting proteins.

Algorithms↗
PubMed2007

Modelling the checkpoint response to telomere uncapping in budding yeast.

One of the DNA damage-response mechanisms in budding yeast is temporary cell-cycle arrest while DNA repair takes place. The DNA damage response requires the coordinated interaction between DNA repair and checkpoint pathways. Telomeres of budding yeast are capped by the Cdc13 complex. In the temperature-sensitive cdc13-1 strain, telomeres are unprotected over a specific temperature range leading to activation of the DNA damage response and subsequently cell-cycle arrest. Inactivation of cdc13-1 results in the generation of long regions of single-stranded DNA (ssDNA) and is affected by the activity of various checkpoint proteins and nucleases. This paper describes a mathematical model of how uncapped telomeres in budding yeast initiate the checkpoint pathway leading to cell-cycle arrest. The model was encoded in the Systems Biology Markup Language (SBML) and simulated using the stochastic simulation system Biology of Ageing e-Science Integration and Simulation (BASIS). Each simulation follows the time course of one mother cell keeping track of the number of cell divisions, the level of activity of each of the checkpoint proteins, the activity of nucleases and the amount of ssDNA generated. The model can be used to carry out a variety of in silico experiments in which different genes are knocked out and the results of simulation are compared to experimental data. Possible extensions to the model are also discussed.

Cell Cycle↗
PubMed2002

Conceptual data modelling for bioinformatics.

Current research in the biosciences depends heavily on the effective exploitation of huge amounts of data. These are in disparate formats, remotely dispersed, and based on the different vocabularies of various disciplines. Furthermore, data are often stored or distributed using formats that leave implicit many important features relating to the structure and semantics of the data. Conceptual data modelling involves the development of implementation-independent models that capture and make explicit the principal structural properties of data. Entities such as a biopolymer or a reaction, and their relations, eg catalyses, can be formalised using a conceptual data model. Conceptual models are implementation-independent and can be transformed in systematic ways for implementation using different platforms, eg traditional database management systems. This paper describes the basics of the most widely used conceptual modelling notations, the ER (entity-relationship) model and the class diagrams of the UML (unified modelling language), and illustrates their use through several examples from bioinformatics. In particular, models are presented for protein structures and motifs, and for genomic sequences.

Computational Biology↗
PubMed2006

Solving structures of protein complexes by molecular replacement with Phaser.

Molecular replacement (MR) generally becomes more difficult as the number of components in the asymmetric unit requiring separate MR models (i.e. the dimensionality of the search) increases. When the proportion of the total scattering contributed by each search component is small, the signal in the search for each component in isolation is weak or non-existent. Maximum-likelihood MR functions enable complex asymmetric units to be built up from individual components with a ;tree search with pruning' approach. This method, as implemented in the automated search procedure of the program Phaser, has been very successful in solving many previously intractable MR problems. However, there are a number of cases in which the automated search procedure of Phaser is suboptimal or encounters difficulties. These include cases where there are a large number of copies of the same component in the asymmetric unit or where the components of the asymmetric unit have greatly varying B factors. Two case studies are presented to illustrate how Phaser can be used to best advantage in the standard ;automated MR' mode and two case studies are used to show how to modify the automated search strategy for problematic cases.

Algorithms↗
PubMed1998

Advanced query mechanisms for biological databases.

Existing query interfaces for biological databases are either based on fixed forms or textual query languages. Users of a fixed form-based query interface are limited to performing some pre-defined queries providing a fixed view of the underlying database, while users of a free text query language-based interface have to understand the underlying data models, specific query languages and application schemas in order to formulate queries. Further, operations on application-specific complex data (e.g., DNA sequences, proteins), which are usually provided by a variety of software packages with their own format requirements and peculiarities, are not available as part of, nor integrated with biological query interfaces. In this paper, we describe generic tools that provide powerful and flexible support for interactively exploring biological databases in a uniform and consistent way, that is via common data models, formats, and notations, in the framework of the Object-Protocol Model (OPM). These tools include (i) a Java graphical query construction tool with support for automatic generation of Web query forms that can be either used for further specifying conditions, or can be saved and customized; (ii) query processors for interpreting and executing queries that may involve complex application-specific objects, and that could span multiple heterogeneous databases and file systems; and (iii) utilities for automatic generation of HTML pages containing query results, that can be browsed using a Web browser. These tools avoid the restrictions imposed by traditional fixed-form query interfaces, while providing users with simple and intuitive facilities for formulating ad-hoc queries across heterogeneous databases, without the need to understand the underlying data models and query languages.

Animals↗
PubMed2005

A graphic tool for curating molecular interaction networks from the literature.

We propose a graphic tool for curating molecular interaction networks constructed from the literature by information extraction (IE). In order to turn preliminary results from IE into useful biomedical resources, we propose to use a controlled environment in which visualization and IE work synergistically. The usability of the proposed graphic tool is shown with respect to the identification of incorrectly extracted results that are due to the much troubling coordination phenomena in natural language texts. Through the experiment on molecular interactions in Saccaharomyces cerevisiae, we have seen a meaningful increase (from 91.5% to 97.5%) in the number of correctly extracted interaction information.

Computational Biology↗
PubMed2005

MeSHer: identifying biological concepts in microarray assays based on PubMed references and MeSH terms.

UNLABELLED: MeSHer uses a simple statistical approach to identify biological concepts in the form of Medical Subject Headings (MeSH terms) obtained from the PubMed database that are significantly overrepresented within the identified gene set relative to those associated with the overall collection of genes on the underlying DNA microarray platform. As a demonstration, we apply this approach to gene lists acquired from a published study of the effects of angiotensin II (Ang II) treatment on cardiac gene expression and demonstrate that this approach can aid in the interpretation of the resulting 'significant' gene set. AVAILABILITY: The software is available at http://www.tm4.org. SUPPLEMENTARY INFORMATION: Results from the analysis of significant genes from the published Ang II study.

Artificial Intelligence↗
PubMed2005

Competitive hybridization kinetics reveals unexpected behavior patterns.

Although the kinetics of hybridization between a soluble polynucleotide and an immobilized complementary sequence have been studied by others, it is almost universally assumed that the interaction between each probe/target pair can be treated as a separate event. This simplifies the mathematics considerably, but it can give a false picture of the extent of hybridization that one achieves at equilibrium as well as the relative quantities of each hybridized pair during the approach to equilibrium. Here we solve the relevant kinetics equations simultaneously using Mathematica as a simulation language. Among the interesting results of this study are that, for certain circumstances, the relative ratio of incorrect to correct hybrids can change dramatically with time; that the relative abundances of two pairs are not what one would expect based on their equilibrium dissociation constants; that the volume of a wash solution after hybridization can have a large effect on results; and the fact that a short wash is typically better than a long one. We show that an optimum wash time exists for a given set of conditions. In addition, the ratio of soluble to insoluble (spotted) molecules can influence results substantially. Finally, the true levels of rare transcripts can be masked by the presence of highly abundant ones. Code is supplied to enable others to study conditions beyond those presented in this article.

Base Composition↗
PubMed1998

Calculating the exact probability of language-like patterns in biomolecular sequences.

We present algorithms for the exact computation of the probability that a random string of a certain length matches a given regular expression. These algorithms can be used to determine statistical significance in a variety of pattern searches such as motif searches and gene-finding. This work improves upon work of Kleffe and Langebacker (Kleffe & Langbecker 1990) and of Sewell and Durbin (Sewell & Durbin 1995) in several ways. First, in many cases of interest, the algorithms presented here are faster. In addition, the type of pattern considered here strictly includes those of both previous works but also allows, for instance, arbitrary length gaps. Also, the type of probability model which can be used is more general than that of Sewell and Durbin, allowing for Markov chains. The problem solved in this work is in fact in the class of NP-hard problems which are believed to be intractable. However, the problem is fixed-parameter tractable, meaning that it is tractable for small patterns. The is problem is also computationally feasible for many patterns which occur in practice. As a sample application, we consider calculating the statistical significance of most of the PROSITE patterns as in Sewell and Durbin. Whereas their method was only fast enough to exactly compute the probabilities for sequences of length 13 larger than the pattern length, we calculate these probabilities for sequences of up to length 2000. In addition, we calculate most of these probabilities using a first order Markov chain. Most of the PROSITE patterns have high significance at length 2000 under both the i.i.d. and Markov chain models. For further applications, we demonstrate the calculation of the probability of a PROSITE pattern occurring on either strand of a random DNA sequence of up to 500 kilo-bases and the probability of a simple gene model occurring in a random sequence of up to 1 megabase.

Algorithms↗
PubMed1991

On the skew distribution of immunoglobulins and the inverted protein-folding problem.

The question of antibody specificity is discussed in the framework of the inverted protein-folding problem (i.e. the characterization of protein sequences with a common fold). A stochastic model of the immune response, patterned after a model for the distribution of words in natural languages is proposed. It is shown that the steady-state probability distribution of immunoglobulin variable-region frequencies is the Yule distribution.

Antibody Specificity↗