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PubMed2005

Global mapping of the protein structure space and application in structure-based inference of protein function.

We have constructed a map of the "protein structure space" by using the pairwise structural similarity scores calculated for all nonredundant protein structures determined experimentally. As expected, proteins with similar structures clustered together in the map and the overall distribution of structural classes of this map followed closely that of the map of the "protein fold space" we have reported previously. Consequently, proteins sharing similar molecular functions also were found to colocalize in the protein structure space map, pointing toward a previously undescribed scheme for structure-based functional inference for remote homologues based on the proximity in the map of the protein structure space. We found that this scheme consistently outperformed other predictions made by using either the raw scores or normalized Z-scores of pairwise DALI structure alignment.

Proteins↗
PubMed2004

ArrayProspector: a web resource of functional associations inferred from microarray expression data.

DNA microarray experiments have provided vast amounts of data which can be used for inferring gene function. However, most methods for predicting functional associations between genes from expression data are not suited to simultaneous analysis of multiple datasets, and a comprehensive resource of coexpression-based predictions is currently lacking. Here, we present an interactive web resource of gene associations predicted by applying a novel algorithm to all expression data in the Stanford Microarray Database. The underlying pre-computed database currently contains more than 200 000 high-confidence gene associations in 12 different species sampled from a broad taxonomic range. The resource allows every association to be inspected visually and can be accessed at http://www.bork.embl.de/ArrayProspector.

Algorithms↗
PubMed2006

In vivo cranial suture function and suture morphology in the extant fish Polypterus: implications for inferring skull function in living and fossil fish.

This study describes the mechanical role that cranial sutures play in fish during feeding. The long-term goal of our work is to establish relationships between suture form and function, so that functional inferences can be made from suture morphology in fossil taxa. To this end, strain gauges were surgically implanted across selected sutures in the skull roof of four individuals of Polypterus endlicherii. After surgery, bone and suture strains during feeding were recorded along with high-speed video of the feeding events. Each trial was designated as a suction feeding or biting on prey trial, and neurocranial elevation, hyoid position and gape were quantified to aid in interpreting the strain data. The strains due to suction feeding are different from those observed during biting. Suction feeding results in a fairly stereotyped strain pattern, with the interfrontal and frontoparietal sutures experiencing tension, while the interparietal suture is compressed. Biting causes much more variable strain patterns. However, both suction and biting result in compression in the back of the skull, and tension between the frontals. Peak strains, and the time at which they occur in the feeding cycle, were compared between suction and biting. In general, peak suture strains are higher during suction than during biting, but not all of these differences are significant. Peak suture and bone strains occur at or near maximum gape during both suction and biting, suggesting that these strains are caused by muscle contraction involved in mouth opening and closing. Micro-computed tomography (microCT) scans of the experimental specimens indicate that the interfrontal and frontoparietal sutures, typically loaded in tension, are less interdigitated in cross section than the interparietal suture, which experiences compression. This is consistent with published correlations of suture form and function in mammals, where interdigitated sutures indicate compression and lack of interdigitation is associated with tension.

Animals↗
PubMed2003

Sequence divergence, functional constraint, and selection in protein evolution.

The genome sequences of multiple species has enabled functional inferences from comparative genomics. A primary objective is to infer biological functions from the conservation of homologous DNA sequences between species. A second, more difficult, objective is to understand what functional DNA sequences have changed over time and are responsible for species' phenotypic differences. The neutral theory of molecular evolution provides a theoretical framework in which both objectives can be explicitly tested. Development of statistical tests within this framework has provided insight into the evolutionary forces that constrain and in some cases change DNA sequences and the resulting patterns that emerge. In this article, we review recent work on how functional constraint and changes in protein function are inferred from protein polymorphism and divergence data. We relate these studies to our understanding of the neutral theory and adaptive evolution.

DNA↗
PubMed2002

Evaluating functional network inference using simulations of complex biological systems.

MOTIVATION: Although many network inference algorithms have been presented in the bioinformatics literature, no suitable approach has been formulated for evaluating their effectiveness at recovering models of complex biological systems from limited data. To overcome this limitation, we propose an approach to evaluate network inference algorithms according to their ability to recover a complex functional network from biologically reasonable simulated data. RESULTS: We designed a simulator to generate data representing a complex biological system at multiple levels of organization: behaviour, neural anatomy, brain electrophysiology, and gene expression of songbirds. About 90% of the simulated variables are unregulated by other variables in the system and are included simply as distracters. We sampled the simulated data at intervals as one would sample from a biological system in practice, and then used the sampled data to evaluate the effectiveness of an algorithm we developed for functional network inference. We found that our algorithm is highly effective at recovering the functional network structure of the simulated system-including the irrelevance of unregulated variables-from sampled data alone. To assess the reproducibility of these results, we tested our inference algorithm on 50 separately simulated sets of data and it consistently recovered almost perfectly the complex functional network structure underlying the simulated data. To our knowledge, this is the first approach for evaluating the effectiveness of functional network inference algorithms at recovering models from limited data. Our simulation approach also enables researchers a priori to design experiments and data-collection protocols that are amenable to functional network inference.

Adaptation, Physiological↗
PubMed2003

Inferring higher functional information for RIKEN mouse full-length cDNA clones with FACTS.

FACTS (Functional Association/Annotation of cDNA Clones from Text/Sequence Sources) is a semiautomated knowledge discovery and annotation system that integrates molecular function information derived from sequence analysis results (sequence inferred) with functional information extracted from text. Text-inferred information was extracted from keyword-based retrievals of MEDLINE abstracts and by matching of gene or protein names to OMIM, BIND, and DIP database entries. Using FACTS, we found that 47.5% of the 60,770 RIKEN mouse cDNA FANTOM2 clone annotations were informative for text searches. MEDLINE queries yielded molecular interaction-containing sentences for 23.1% of the clones. When disease MeSH and GO terms were matched with retrieved abstracts, 22.7% of clones were associated with potential diseases, and 32.5% with GO identifiers. A significant number (23.5%) of disease MeSH-associated clones were also found to have a hereditary disease association (OMIM Morbidmap). Inferred neoplastic and nervous system disease represented 49.6% and 36.0% of disease MeSH-associated clones, respectively. A comparison of sequence-based GO assignments with informative text-based GO assignments revealed that for 78.2% of clones, identical GO assignments were provided for that clone by either method, whereas for 21.8% of clones, the assignments differed. In contrast, for OMIM assignments, only 28.5% of clones had identical sequence-based and text-based OMIM assignments. Sequence, sentence, and term-based functional associations are included in the FACTS database (http://facts.gsc.riken.go.jp/), which permits results to be annotated and explored through web-accessible keyword and sequence search interfaces. The FACTS database will be a critical tool for investigating the functional complexity of the mouse transcriptome, cDNA-inferred interactome (molecular interactions), and pathome (pathologies).

Animals↗
PubMed1999

Testing an inference of function from structure: snake vertebrae do the twist.

The zygapophyses and zygosphene-zygantrum articulations of snake vertebrae are hypothesized to restrict or eliminate vertebral torsion. This hypothesis is apparently based solely on the inference of function from structure, despite the limitations of such inferences, as well as contradictory observations and measurements. In this study, I observed and measured axial torsion in gopher snakes, Pituophis melanoleucus. To examine the structural basis of axial torsion, I measured the vertebral articulation angles along the body and the insertion angles of five epaxial muscles. To examine torsion in a natural behavior, I digitized video images and measured the degree of apparent axial torsion during terrestrial lateral undulation. Finally, I measured the mechanical capacity of the vertebral joints for actual torsion over intervals of 10 vertebrae in fresh, skinned segments of the trunk. Vertebral articulation angles vary up to 30 degrees and are associated with variation in torsional capacity along the trunk. The freely crawling P. melanoleucus twisted up to 2.19 degrees per vertebra, which produced substantial overall torsion when added over several vertebrae. The vertebral joints are mechanically capable of torsion up to 2.89 degrees per joint. Therefore, despite the mechanical restriction imposed by the complex articulations, vertebral torsion occurs in snakes and appears to be functionally important in several natural behaviors. Even in cases in which mechanical function appears to be narrowly constrained by morphology, specific functions should not be inferred solely from structural analyses.

Animals↗
PubMed1999

Testing two mechanisms by which rational and irrational beliefs may affect the functionality of inferences.

This article describes a role playing experiment that examined the sufficiency hypothesis of Rational Emotive Behaviour Therapy (REBT). This proposition states that it is sufficient for rational and irrational beliefs to refer to preferences and musts, respectively, if those beliefs are to affect the functionality of inferences (FI). Consistent with the REBT literature (e.g. Dryden, 1994; Dryden & Ellis, 1988; Palmer, Dryden, Ellis & Yapp, 1995) results from this experiment showed that rational and irrational beliefs, as defined by REBT, do affect FI. Specifically, results showed that people who hold a rational belief form inferences that are significantly more functional than those that are formed by people who hold an irrational belief. Contrary to REBT theory, the sufficiency hypothesis was not supported. Thus, results indicated that it is not sufficient for rational and irrational beliefs to refer to preferences and musts, respectively, if those beliefs are to affect the FI. It appears, then, that preferences and musts are not sufficient mechanisms by which rational and irrational beliefs, respectively, affect the FI. Psychotherapeutic implications of these findings are considered.

Adult↗
PubMed2004

Multilevel linear modelling for FMRI group analysis using Bayesian inference.

Functional magnetic resonance imaging studies often involve the acquisition of data from multiple sessions and/or multiple subjects. A hierarchical approach can be taken to modelling such data with a general linear model (GLM) at each level of the hierarchy introducing different random effects variance components. Inferring on these models is nontrivial with frequentist solutions being unavailable. A solution is to use a Bayesian framework. One important ingredient in this is the choice of prior on the variance components and top-level regression parameters. Due to the typically small numbers of sessions or subjects in neuroimaging, the choice of prior is critical. To alleviate this problem, we introduce to neuroimage modelling the approach of reference priors, which drives the choice of prior such that it is noninformative in an information-theoretic sense. We propose two inference techniques at the top level for multilevel hierarchies (a fast approach and a slower more accurate approach). We also demonstrate that we can infer on the top level of multilevel hierarchies by inferring on the levels of the hierarchy separately and passing summary statistics of a noncentral multivariate t distribution between them.

Bayes Theorem↗
PubMed2005

Nebulon: a system for the inference of functional relationships of gene products from the rearrangement of predicted operons.

Since operons are unstable across Prokaryotes, it has been suggested that perhaps they re-combine in a conservative manner. Thus, genes belonging to a given operon in one genome might re-associate in other genomes revealing functional relationships among gene products. We developed a system to build networks of functional relationships of gene products based on their organization into operons in any available genome. The operon predictions are based on inter-genic distances. Our system can use different kinds of thresholds to accept a functional relationship, either related to the prediction of operons, or to the number of non-redundant genomes that support the associations. We also work by shells, meaning that we decide on the number of linking iterations to allow for the complementation of related gene sets. The method shows high reliability benchmarked against knowledge-bases of functional interactions. We also illustrate the use of Nebulon in finding new members of regulons, and of other functional groups of genes. Operon rearrangements produce thousands of high-quality new interactions per prokaryotic genome, and thousands of confirmations per genome to other predictions, making it another important tool for the inference of functional interactions from genomic context.

Bacterial Proteins↗
PubMed2006

Combining gene expression profiles and protein-protein interaction data to infer gene functions.

The ever-increasing flow of gene expression profiles and protein-protein interactions has catalyzed many computational approaches for inference of gene functions. Despite all the efforts, there is still room for improvement, for the information enriched in each biological data source has not been exploited to its fullness. A composite method is proposed for classifying unannotated genes based on expression data and protein-protein interaction (PPI) data, which extracts information from both data sources in novel ways. With the noise nature of expression data taken into consideration, importance is attached to the consensus expression patterns of gene classes instead of the actual expression profiles of individual genes, thus characterizing the composite method with enhanced robustness against microarray data variation. With regard to the PPI network, the traditional clear-cut binary attitude towards inter- and intra-functional interactions is abandoned, whereas a more objective perspective into the PPI network structure is formed through incorporating the varied function-function interaction probabilities into the algorithm. The composite method was implemented in two numerical experiments, where its improvement over single-data-source based methods was observed and the superiority of the novel data handling operations was discussed.

Algorithms↗
PubMed2002

Operon conservation from the point of view of Escherichia coli, and inference of functional interdependence of gene products from genome context.

We have previously demonstrated that genes within experimentally characterized operons of Escherichia coli are conserved together in other genomes more frequently than genes at the borders of transcription units. Here we expand the analyses and show that, as the phylogenetic distance of the genomes compared increases, the genes remaining together must belong to genes associated into operons in other prokaryotes regardless of the operon organization of the corresponding orthologous gene pair of E. coli. At the same time, we show that the observed tendencies of genes within operons to keep very short inter-genic distances in E. coli, is the same in any other prokaryote whose genome is currently available. We also show the relationship between our analyses of conservation and the inference of functional relationships from genomic context.

Computational Biology↗
PubMed2004

Enhanced functional and structural domain assignments using remote similarity detection procedures for proteins encoded in the genome of Mycobacterium tuberculosis H37Rv.

The sequencing of the Mycobacterium tuberculosis (MTB) H37Rv genome has facilitated deeper insights into the biology of MTB, yet the functions of many MTB proteins are unknown. We have used sensitive profile-based search procedures to assign functional and structural domains to infer functions of gene products encoded in MTB. These domain assignments have been made using a compendium of sequence and structural domain families. Functions are predicted for 78 % of the encoded gene products. For 69 % of these, functions can be inferred by domain assignments. The functions for the rest are deduced from their homology to proteins of known function. Superfamily relationships between families of unknown and known structures have increased structural information by approximately 11%. Remote similarity detection methods have enabled domain assignments for 1325 'hypothetical proteins'. The most populated families in MTB are involved in lipid metabolism, entry and survival of the bacillus in host. Interestingly, for 353 proteins, which we refer to as MTB-specific, no homologues have been identified. Numerous, previously unannotated, hypothetical proteins have been assigned domains and some of these could perhaps be the possible chemotherapeutic targets. MTB-specific proteins might include factors responsible for virulence. Importantly, these assignments could be valuable for experimental endeavors. The detailed results are publicly available at http://hodgkin.mbu.iisc.ernet.in/~dots.

Amino Acid Sequence↗
PubMed2004

A neuroeconomics approach to inferring utility functions in sensorimotor control.

Making choices is a fundamental aspect of human life. For over a century experimental economists have characterized the decisions people make based on the concept of a utility function. This function increases with increasing desirability of the outcome, and people are assumed to make decisions so as to maximize utility. When utility depends on several variables, indifference curves arise that represent outcomes with identical utility that are therefore equally desirable. Whereas in economics utility is studied in terms of goods and services, the sensorimotor system may also have utility functions defining the desirability of various outcomes. Here, we investigate the indifference curves when subjects experience forces of varying magnitude and duration. Using a two-alternative forced-choice paradigm, in which subjects chose between different magnitude-duration profiles, we inferred the indifference curves and the utility function. Such a utility function defines, for example, whether subjects prefer to lift a 4-kg weight for 30 s or a 1-kg weight for a minute. The measured utility function depends nonlinearly on the force magnitude and duration and was remarkably conserved across subjects. This suggests that the utility function, a central concept in economics, may be applicable to the study of sensorimotor control.

Adult↗
PubMed2002

The advantage of functional prediction based on clustering of yeast genes and its correlation with non-sequence based classifications.

Sequence similarity is probably the most widely used tool to infer functional linkage between proteins. The fully sequenced, much researched, genome of Saccharomyces cerevisiae gives us on opportunity to compare and statistically quantify computational methods based on sequence similarity, which aim to detect such linkage. In addition, the amount of data regarding Saccharomyces Cerevisiae genes and proteins, which is not directly based on sequence is rapidly increasing. Consequently, it allows investigation of the connections and correlation between classification based on these types of data and that based solely on sequence similarity. In this work we start with a simple clustering algorithm to cluster genes based on the BLAST E-score of their similarity. We analyze how well one can infer function from these clusters and for how many of the genes that are currently unknown one can suggest a prediction. Given these parameters, we show that even a simple algorithm achieves better results than simply considering the BLAST output of matching genes. In the second part of the paper, we show that there is a highly significant correlation (p-value < 10(-4) for the vast majority of the experiments) between the aforementioned clusters and other types of classifications. Namely, we show that a pair of genes being clustered together is correlated with these genes having similar expression patterns in DNA array experiments and with the encoded proteins being involved in protein-protein interactions. Although this correlation is highly significant, it is, of course, not strong enough to be, by itself, a tool for predicting co-regulation of genes or interaction of proteins. We discuss possible explanations for this correlation. Furthermore, the statistical evaluation of these results should be considered when developing tools that are aimed at making such predictions.

Algorithms↗
PubMed2006

Forward inference using functional neuroimaging: dissociations versus associations.

Many people are excited by functional neuroimaging as a new tool for cognitive science; many others are sceptical. In this opinion article, I describe a 'forward inference' that one can make from patterns of brain activity to distinguish between cognitive theories. I give an example of forward inferences in research on recognition memory, and outline some statistical criteria for a 'qualitative difference' in brain activity. Forward inferences resemble the dissociation logic long-used in behavioural studies of healthy and brain-damaged people, although I argue that dissociations in neuroimaging data can go beyond behavioural dissociations. Nonetheless, forward inferences are only as good as the cognitive theories to which they pertain, and are most valuable in conjunction with other types of inference.

Association↗
PubMed2006

In search of functional association from time-series microarray data based on the change trend and level of gene expression.

BACKGROUND: The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional linkages between genes from expression data are mainly based on a point-to-point comparison. Change trends between consecutive time points in time-series data have been so far not well explored. RESULTS: In this work we present a new method based on extracting main features of the change trend and level of gene expression between consecutive time points. The method, termed as trend correlation (TC), includes two major steps: 1, calculating a maximal local alignment of change trend score by dynamic programming and a change trend correlation coefficient between the maximal matched change levels of each gene pair; 2, inferring relationships of gene pairs based on two statistical extraction procedures. The new method considers time shifts and inverted relationships in a similar way as the local clustering (LC) method but the latter is merely based on a point-to-point comparison. The TC method is demonstrated with data from yeast cell cycle and compared with the LC method and the widely used Pearson correlation coefficient (PCC) based clustering method. The biological significance of the gene pairs is examined with several large-scale yeast databases. Although the TC method predicts an overall lower number of gene pairs than the other two methods at a same p-value threshold, the additional number of gene pairs inferred by the TC method is considerable: e.g. 20.5% compared with the LC method and 49.6% with the PCC method for a p-value threshold of 2.7E-3. Moreover, the percentage of the inferred gene pairs consistent with databases by our method is generally higher than the LC method and similar to the PCC method. A significant number of the gene pairs only inferred by the TC method are process-identity or function-similarity pairs or have well-documented biological interactions, including 443 known protein interactions and some known cell cycle related regulatory interactions. It should be emphasized that the overlapping of gene pairs detected by the three methods is normally not very high, indicating a necessity of combining the different methods in search of functional association of genes from time-series data. For a p-value threshold of 1E-5 the percentage of process-identity and function-similarity gene pairs among the shared part of the three methods reaches 60.2% and 55.6% respectively, building a good basis for further experimental and functional study. Furthermore, the combined use of methods is important to infer more complete regulatory circuits and network as exemplified in this study. CONCLUSION: The TC method can significantly augment the current major methods to infer functional linkages and biological network and is well suitable for exploring temporal relationships of gene expression in time-series data.

Algorithms↗