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A consensus procedure for predicting the location of alpha-helical transmembrane segments in proteins.

To aid in the development of three-dimensional models of membrane-bound proteins, a consensus procedure for predicting alpha-helical transmembrane segments from amino acid sequence is presented. The algorithm combines the results of six individual prediction methods and some basic properties of membrane-spanning helices to obtain a final consensus prediction. Comparison with experiment and several other recently developed methods shows that the consensus procedure performs quite well in comparison to other recent methods. A FORTRAN program has been developed which takes an input file containing an amino acid sequence in one-letter code and outputs a list of the alpha-helical transmembrane segments predicted by the consensus algorithm.

Algorithms↗

Extraction of biological interaction networks from scientific literature.

Biology can be regarded as a science of networks: interactions between various biological entities (eg genes, proteins, metabolites) on different levels (eg gene regulation, cell signalling) can be represented as graphs and, thus, analysis of such networks might shed new light on the function of biological systems. Such biological networks can be obtained from different sources. The extraction of networks from text is an important technique that requires the integration of several different computational disciplines. This paper summarises the most important steps in network extraction and reviews common approaches and solutions for the extraction of biological networks from scientific literature.

Abstracting and Indexing↗

Search for a new description of protein topology and local structure.

A novel description of protein structure in terms of the generalized secondary structure elements (GSSE) is proposed. GSSE's are defined as fragments of the protein structure where the chain doesn't radically change its direction. In this new language, global protein topology becomes a particular arrangement of the relatively small number of large, rod like GSSE's. Protein topology can be described by an adjacency matrix giving information, which GSSE's are close in space to each other and defining a graph, where GSSE's are equivalent to vertices and interactions between them to edges. The information about the local structure is translated into the local density of pseudo-Calpha atoms along the chain and the curvature of the chain. This new description has a number of interesting and useful features. For instance, enumeration theorems of graph theory can be used to estimate a number of possible topologies for a protein built from a given number of elements. Different topologies, including novel ones, can be generated from the known by various permutations of elements. Many new regularities in protein structures become suddenly visible in a new description. A new local structure description is more amenable to predictions and easier to use in fold predictions.

Animals↗

MiGenes: a searchable interspecies database of mitochondrial proteins curated using gene ontology annotation.

MOTIVATION: There has been an explosion of interest in the role of mitochondria in programmed cell death and other fundamental pathological processes underlying the development of human diseases. Nevertheless, the inventory of mitochondrial proteins encoded in the nuclear genome remains incomplete, providing an impediment to mitochondrial research at the interface with systems biology. We created the MiGenes database to further define the scope of the mitochondrial proteome in humans and model organisms including mice, rats, flies and worms as well as budding and fission yeasts. MiGenes is intended to stimulate mitochondrial research using model organisms. SUMMARY: MiGenes is a large-scale relational database that is automatically updated to keep pace with advances in mitochondrial proteomics and is curated to assure that the designation of proteins as mitochondrial reflects gene ontology (GO) annotations supported by high-quality evidence codes. A set of postulates is proposed to help define which proteins are authentic components of mitochondria. MiGenes incorporates >1160 new GO annotations to human, mouse and rat protein records, 370 of which represent the first GO annotation reflecting a mitochondrial localization. MiGenes employs a flexible search interface that permits batchwise accession number searches to support high-throughput proteomic studies. A web interface is provided to permit members of the mitochondrial research community to suggest modifications in protein annotations or mitochondrial status.

Animals↗

MDB: a database system utilizing automatic construction of modules and STAR-derived universal language.

MOTIVATION: The value of information greatly increases if stored in databases. The objective was to construct a multi-purpose database system primarily designed to store and provide access to three-dimensional structures of biological molecules including theoretical models. RESULTS: A dictionary defining data format and structure for three-dimensional models of biological molecules (MDB dictionary) was developed. The dictionary was written using universal, standardized data description language. This language can be applied to describe data with no restrictions on their origin or type, including metadata. Thus both the data definitions (format) and database descriptions are created using the uniform language and processed with universal software. A database and data design technique that allowed use of dictionaries to automatically construct relational databases was developed. This technique was employed to construct the MDB database system. Data design developed and applied in the MDB project makes it possible to carry out data curation utilizing the database engine to identify errors. It also allows storage and query of data at different levels of consistency with the standard format specifications, i.e. both the correctly formatted data, and data that requires further curation. AVAILABILITY: The MDB dictionary is available at http://www.gwer.ch/proteinstructure/mdb and as part of the PDB resources at http://pdb.rutgers.edu/mmcif/.

Computational Biology↗

Gene annotation from scientific literature using mappings between keyword systems.

MOTIVATION: The description of genes in databases by keywords helps the non-specialist to quickly grasp the properties of a gene and increases the efficiency of computational tools that are applied to gene data (e.g. searching a gene database for sequences related to a particular biological process). However, the association of keywords to genes or protein sequences is a difficult process that ultimately implies examination of the literature related to a gene. RESULTS: To support this task, we present a procedure to derive keywords from the set of scientific abstracts related to a gene. Our system is based on the automated extraction of mappings between related terms from different databases using a model of fuzzy associations that can be applied with all generality to any pair of linked databases. We tested the system by annotating genes of the SWISS-PROT database with keywords derived from the abstracts linked to their entries (stored in the MEDLINE database of scientific references). The performance of the annotation procedure was much better for SWISS-PROT keywords (recall of 47%, precision of 68%) than for Gene Ontology terms (recall of 8%, precision of 67%). AVAILABILITY: The algorithm can be publicly accessed and used for the annotation of sequences through a web server at http://www.bork.embl.de/kat

Abstracting and Indexing↗

Recognizing names in biomedical texts using mutual information independence model and SVM plus sigmoid.

In this paper, we present a biomedical name recognition system, called PowerBioNE. In order to deal with the special phenomena in the biomedical domain, various evidential features are proposed and integrated through a mutual information independence model (MIIM). In addition, a support vector machine (SVM) plus sigmoid is proposed to resolve the data sparseness problem in the MIIM. In this way, the data sparseness problem in MIIM-based biomedical name recognition can be resolved effectively and a biomedical name recognition system with better performance and better portability can be achieved. Finally, we present two post-processing modules to deal with the nested entity name and abbreviation phenomena in the biomedical domain to further improve the performance. Evaluation shows that our system achieves F-measures of 69.1 and 71.2 on the 23 classes of GENIA V1.1 and V3.0, respectively. In particular, our system achieves an F-measure of 77.8 on the "protein" class of GENIA V3.0. It also shows that our system outperforms the best-reported system on GENIA V1.1 and V3.0.

Abstracting and Indexing↗

The genetics of autism.

Autism is a complex, behaviorally defined, static disorder of the immature brain that is of great concern to the practicing pediatrician because of an astonishing 556% reported increase in pediatric prevalence between 1991 and 1997, to a prevalence higher than that of spina bifida, cancer, or Down syndrome. This jump is probably attributable to heightened awareness and changing diagnostic criteria rather than to new environmental influences. Autism is not a disease but a syndrome with multiple nongenetic and genetic causes. By autism (the autistic spectrum disorders [ASDs]), we mean the wide spectrum of developmental disorders characterized by impairments in 3 behavioral domains: 1) social interaction; 2) language, communication, and imaginative play; and 3) range of interests and activities. Autism corresponds in this article to pervasive developmental disorder (PDD) of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition and International Classification of Diseases, Tenth Revision. Except for Rett syndrome--attributable in most affected individuals to mutations of the methyl-CpG-binding protein 2 (MeCP2) gene--the other PDD subtypes (autistic disorder, Asperger disorder, disintegrative disorder, and PDD Not Otherwise Specified [PDD-NOS]) are not linked to any particular genetic or nongenetic cause. Review of 2 major textbooks on autism and of papers published between 1961 and 2003 yields convincing evidence for multiple interacting genetic factors as the main causative determinants of autism. Epidemiologic studies indicate that environmental factors such as toxic exposures, teratogens, perinatal insults, and prenatal infections such as rubella and cytomegalovirus account for few cases. These studies fail to confirm that immunizations with the measles-mumps-rubella vaccine are responsible for the surge in autism. Epilepsy, the medical condition most highly associated with autism, has equally complex genetic/nongenetic (but mostly unknown) causes. Autism is frequent in tuberous sclerosis complex and fragile X syndrome, but these 2 disorders account for but a small minority of cases. Currently, diagnosable medical conditions, cytogenetic abnormalities, and single-gene defects (eg, tuberous sclerosis complex, fragile X syndrome, and other rare diseases) together account for <10% of cases. There is convincing evidence that "idiopathic" autism is a heritable disorder. Epidemiologic studies report an ASD prevalence of approximately 3 to 6/1000, with a male to female ratio of 3:1. This skewed ratio remains unexplained: despite the contribution of a few well characterized X-linked disorders, male-to-male transmission in a number of families rules out X-linkage as the prevailing mode of inheritance. The recurrence rate in siblings of affected children is approximately 2% to 8%, much higher than the prevalence rate in the general population but much lower than in single-gene diseases. Twin studies reported 60% concordance for classic autism in monozygotic (MZ) twins versus 0 in dizygotic (DZ) twins, the higher MZ concordance attesting to genetic inheritance as the predominant causative agent. Reevaluation for a broader autistic phenotype that included communication and social disorders increased concordance remarkably from 60% to 92% in MZ twins and from 0% to 10% in DZ pairs. This suggests that interactions between multiple genes cause "idiopathic" autism but that epigenetic factors and exposure to environmental modifiers may contribute to variable expression of autism-related traits. The identity and number of genes involved remain unknown. The wide phenotypic variability of the ASDs likely reflects the interaction of multiple genes within an individual's genome and the existence of distinct genes and gene combinations among those affected. There are 3 main approaches to identifying genetic loci, chromosomal regions likely to contain relevant genes: 1) whole genome screens, searching for linkage of autism to shared genetic markers in populations of multiplex families (families with >1 affected family member; 2) cytogenetic studies that may guide molecular studies by pointing to relevant inherited or de novo chromosomal abnormalities in affected individuals and their families; and 3) evaluation of candidate genes known to affect brain development in these significantly linked regions or, alternatively, linkage of candidate genes selected a priori because of their presumptive contribution to the pathogenesis of autism. Data from whole-genome screens in multiplex families suggest interactions of at least 10 genes in the causation of autism. Thus far, a putative speech and language region at 7q31-q33 seems most strongly linked to autism, with linkages to multiple other loci under investigation. Cytogenetic abnormalities at the 15q11-q13 locus are fairly frequent in people with autism, and a "chromosome 15 phenotype" was described in individuals with chromosome 15 duplications. Among other candidate genes are the FOXP2, RAY1/ST7, IMMP2L, and RELN genes at 7q22-q33 and the GABA(A) receptor subunit and UBE3A genes on chromosome 15q11-q13. Variant alleles of the serotonin transporter gene (5-HTT) on 17q11-q12 are more frequent in individuals with autism than in nonautistic populations. In addition, animal models and linkage data from genome screens implicate the oxytocin receptor at 3p25-p26. Most pediatricians will have 1 or more children with this disorder in their practices. They must diagnose ASD expeditiously because early intervention increases its effectiveness. Children with dysmorphic features, congenital anomalies, mental retardation, or family members with developmental disorders are those most likely to benefit from extensive medical testing and genetic consultation. The yield of testing is much less in high-functioning children with a normal appearance and IQ and moderate social and language impairments. Genetic counseling justifies testing, but until autism genes are identified and their functions are understood, prenatal diagnosis will exist only for the rare cases ascribable to single-gene defects or overt chromosomal abnormalities. Parents who wish to have more children must be told of their increased statistical risk. It is crucial for pediatricians to try to involve families with multiple affected members in formal research projects, as family studies are key to unraveling the causes and pathogenesis of autism. Parents need to understand that they and their affected children are the only available sources for identifying and studying the elusive genes responsible for autism. Future clinically useful insights and potential medications depend on identifying these genes and elucidating the influences of their products on brain development and physiology.

Autistic Disorder↗

A word-oriented approach to alignment validation.

MOTIVATION: Multiple sequence alignment at the level of whole proteomes requires a high degree of automation, precluding the use of traditional validation methods such as manual curation. Since evolutionary models are too general to describe the history of each residue in a protein family, there is no single algorithm/model combination that can yield a biologically or evolutionarily optimal alignment. We propose a 'shotgun' strategy where many different algorithms are used to align the same family, and the best of these alignments is then chosen with a reliable objective function. We present WOOF, a novel 'word-oriented' objective function that relies on the identification and scoring of conserved amino acid patterns (words) between pairs of sequences. RESULTS: Tests on a subset of reference protein alignments from BAliBASE showed that WOOF tended to rank the (manually curated) reference alignment highest among 1060 alternative (automatically generated) alignments for a majority of protein families. Among the automated alignments, there was a strong positive relationship between the WOOF score and similarity to the reference alignment. The speed of WOOF and its independence from explicit considerations of three-dimensional structure make it an excellent tool for analyzing large numbers of protein families. AVAILABILITY: On request from the authors.

Algorithms↗

A genome scan for developmental dyslexia confirms linkage to chromosome 2p11 and suggests a new locus on 7q32.

Developmental dyslexia is a distinct learning disability with unexpected difficulty in learning to read despite adequate intelligence, education, and environment, and normal senses. The genetic aetiology of dyslexia is heterogeneous and loci on chromosomes 2, 3, 6, 15, and 18 have been repeatedly linked to it. We have conducted a genome scan with 376 markers in 11 families with 38 dyslexic subjects ascertained in Finland. Linkage of dyslexia to the vicinity of DYX3 on 2p was confirmed with a non-parametric linkage (NPL) score of 2.55 and a lod score of 3.01 for a dominant model, and a novel locus on 7q32 close to the SPCH1 locus was suggested with an NPL score of 2.77. The SPCH1 locus has previously been linked with a severe speech and language disorder and autism, and a mutation in exon 14 of the FOXP2 gene on 7q32 has been identified in one large pedigree. Because the language disorder associated with the SPCH1 locus has some overlap with the language deficits observed in dyslexia, we sequenced the coding region of FOXP2 as a candidate gene for our observed linkage in six dyslexic subjects. No mutations were identified. We conclude that DYX3 appears to be important for dyslexia susceptibility in many Finnish families, and a suggested linkage of dyslexia to chromosome 7q32 will need verification in other data sets.

Chromosome Mapping↗

Using process diagrams for the graphical representation of biological networks.

With the increased interest in understanding biological networks, such as protein-protein interaction networks and gene regulatory networks, methods for representing and communicating such networks in both human- and machine-readable form have become increasingly important. Although there has been significant progress in machine-readable representation of networks, as exemplified by the Systems Biology Mark-up Language (SBML) (http://www.sbml.org) issues in human-readable representation have been largely ignored. This article discusses human-readable diagrammatic representations and proposes a set of notations that enhances the formality and richness of the information represented. The process diagram is a fully state transition-based diagram that can be translated into machine-readable forms such as SBML in a straightforward way. It is supported by CellDesigner, a diagrammatic network editing software (http://www.celldesigner.org/), and has been used to represent a variety of networks of various sizes (from only a few components to several hundred components).

Animals↗

A hybrid systems framework for cellular processes.

With the availability of technologies that allow us to obtain stimulus-response time series data for modeling and system identification, there is going to be an increasing need for conceptual frameworks in which to formulate and test hypotheses about intra- and inter-cellular dynamics, in general and not just dependent on a particular cell line, cell type, organism, or technology. While the semantics can be quite different, biologists and systems scientists use in many cases a similar language (notion of feedback, regulation, etc.). A more abstract system-theoretic framework for signals, systems, and control could provide the biologist with an interface between the domains. Apart from recent examples to identify functional elements and describing them in engineering terms, there have been various more abstract developments to describe dynamics at the cell level in the past. This includes Rosen's (M,R)-systems. This paper presents an abstract and general compact mathematical framework of intracellular dynamics, regulation and regime switching inspired by (M,R)-theory and based on hybrid automata.

Algorithms↗

Chemical effects in biological systems (CEBS) object model for toxicology data, SysTox-OM: design and application.

MOTIVATION: The CEBS data repository is being developed to promote a systems biology approach to understand the biological effects of environmental stressors. CEBS will house data from multiple gene expression platforms (transcriptomics), protein expression and protein-protein interaction (proteomics), and changes in low molecular weight metabolite levels (metabolomics) aligned by their detailed toxicological context. The system will accommodate extensive complex querying in a user-friendly manner. CEBS will store toxicological contexts including the study design details, treatment protocols, animal characteristics and conventional toxicological endpoints such as histopathology findings and clinical chemistry measures. All of these data types can be integrated in a seamless fashion to enable data query and analysis in a biologically meaningful manner. RESULTS: An object model, the SysBio-OM (Xirasagar et al., 2004) has been designed to facilitate the integration of microarray gene expression, proteomics and metabolomics data in the CEBS database system. We now report SysTox-OM as an open source systems toxicology model designed to integrate toxicological context into gene expression experiments. The SysTox-OM model is comprehensive and leverages other open source efforts, namely, the Standard for Exchange of Nonclinical Data (http://www.cdisc.org/models/send/v2/index.html) which is a data standard for capturing toxicological information for animal studies and Clinical Data Interchange Standards Consortium (http://www.cdisc.org/models/sdtm/index.html) that serves as a standard for the exchange of clinical data. Such standardization increases the accuracy of data mining, interpretation and exchange. The open source SysTox-OM model, which can be implemented on various software platforms, is presented here. AVAILABILITY: A universal modeling language (UML) depiction of the entire SysTox-OM is available at http://cebs.niehs.nih.gov and the Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http://cebs.niehs.nih.gov/cebsdownloads. Currently, the public toxicological data in CEBS can be queried via a web application based on the SysTox-OM at http://cebs.niehs.nih.gov CONTACT: xirasagars@saic.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Computational Biology↗

Statistical and visual morph movie analysis of crystallographic mutant selection bias in protein mutation resource data.

The relationship between protein mutations and conformational change can potentially decipher the language relating sequence to structure. Elsewhere, we presented the Protein Mutant Resource (PMR), an online tool that systematically identified related mutants in the Protein DataBank (PDB), inferred mutant Gene Ontology classifications using data-mining, and allowed intuitive exploration of relationships between mutant structures. Here, we perform a comprehensive statistical analysis of PMR mutants. Although the PMR contains spectacular conformational changes, generally there is a counter-intuitive inverse relationship between conformational change and the number of mutations. That is, PDB mutations contrast naturally evolved mutations. We compare the frequencies of mutations in the PMR/PDB datasets against the PAM250 natural mutation frequencies to confirm this. We make available morph movies from PMR structure pairs, allowing visual analysis of conformational change and the ability to distinguish visually between conformational change due to motions (e.g., ligand binding)and mutations. The PMR is at http://pmr.sdsc.edu.

Bias↗

Drug discovery in the kinase inhibitory field using the Nested Chemical Library technology.

Kinase inhibitors are at the forefront of modern drug research, where mostly three technologies are used for hit-and-lead finding: high throughput screening of random libraries, three-dimensional structure-based drug design based on X-ray data, and focused libraries around limited number of new cores. Our novel Nested Chemical Library (NCL) (Vichem Chemie Research Ltd., Budapest, Hungary) technology is based on a knowledge base approach, where focused libraries around selected cores are used to generate pharmacophore models. NCL was designed on the platform of a diverse kinase inhibitory library organized around 97 core structures. We have established a unique, proprietary kinase inhibitory chemistry around these core structures with small focused sublibraries around each core. All the compounds in our NCL library are stored in a big unified Structured Query Language database along with their measured and calculated physicochemical and ADME/toxicity (ADMET) properties, together with thousands of molecular descriptors calculated for each compound. Biochemical kinase inhibitory assays on selected, cloned kinase enzymes for a few hundred NCL compound sets can provide sufficient biological data for rational computerized design of new analogues, based on our pharmacophore model-generating 3DNET4W QSPAR (quantitative structure-property/activity relationships) approach. Using this pharmacophore modeling approach and the ADMET filters, we can preselect synthesizable compounds for hit-and-lead optimization. Starting from this point and integrating the information from QSPAR, high-quality leads can be generated within a small number of optimization cycles. Applying NCL technology we have developed lead compounds for several validated kinase targets.

Algorithms↗

Body language: the function of PML nuclear bodies in apoptosis regulation.

Promyelocytic leukaemia (PML) nuclear bodies (NBs) are macromolecular nuclear domains present in virtually every mammalian cell. PML nuclear bodies (PML-NBs) were functionally linked to various fundamental cellular processes, including transcriptional control, tumour suppression and apoptosis regulation. Supporting the important function of PML and its associated NBs in apoptosis regulation, several apoptotic regulators localise to PML-NBs, and cells from PML-deficient mice show severe apoptotic defects, including induction of genotoxic stress and death receptor CD95 (Fas/APO-1) activation. Based on the current literature, we hypothesise that PML-NBs regulate apoptosis through different molecular mechanisms, on the one hand by acting as macromolecular scaffolds for recruitment and post-translational modification of the apoptotic key regulator p53, and on the other by regulating the subcellular bioavailability and quality of some apoptotic signal transducers.

Animals↗

Identification of biological relationships from text documents using efficient computational methods.

The biological literature databases continue to grow rapidly with vital information that is important for conducting sound biomedical research and development. The current practices of manually searching for information and extracting pertinent knowledge are tedious, time-consuming tasks even for motivated biological researchers. Accurate and computationally efficient approaches in discovering relationships between biological objects from text documents are important for biologists to develop biological models. The term "object" refers to any biological entity such as a protein, gene, cell cycle, etc. and relationship refers to any dynamic action one object has on another, e.g. protein inhibiting another protein or one object belonging to another object such as, the cells composing an organ. This paper presents a novel approach to extract relationships between multiple biological objects that are present in a text document. The approach involves object identification, reference resolution, ontology and synonym discovery, and extracting object-object relationships. Hidden Markov Models (HMMs), dictionaries, and N-Gram models are used to set the framework to tackle the complex task of extracting object-object relationships. Experiments were carried out using a corpus of one thousand Medline abstracts. Intermediate results were obtained for the object identification process, synonym discovery, and finally the relationship extraction. For the thousand abstracts, 53 relationships were extracted of which 43 were correct, giving a specificity of 81 percent. These results are promising for multi-object identification and relationship finding from biological documents.

Algorithms↗

A combined genetic and biochemical approach to mammalian signal transduction.

The last five years have seen a rapid increase in interest and understanding of signal transduction pathways. While the description of such pathways has become more detailed and complex, a number of consistent findings have emerged. Modular domains, such as SH2 and SH3 domains, are present on a wide variety of proteins and mediate specific protein-protein interactions. By defining the interaction mediated by such domains, a 'language' of interaction between proteins in signalling pathways is emerging. As more signalling proteins are identified it has become apparent that most oncogenes and tumour suppressor genes are components of major signalling pathways. Therefore, studies on the basic biology of signal transduction are having a direct impact on our understanding of cell transformation. With the characterisation of signalling pathways in a range of organisms, it has also become obvious that signalling pathways are ancient and have been highly conserved over the last billion years of evolution. A practical result of this finding has been the ability to exploit results obtained in genetically tractable invertebrate species such as C. elegans and Drosophila melanogaster to investigate signal transduction in mammals. This is an approach we have emphasized in our investigation of signal transduction by tyrosine kinase receptors in human and mouse cells. Results obtained in these studies with the Sos and Siah proteins are reviewed.

Animals↗