Model-based prediction of the individual training intensity for the lower back muscles with application to physical rehabilitation

The individual adjustment of the training intensity during physical training of the lower back muscles plays a crucial role in strength rehabilitation of chronic low back pain patients. Since an one-repetition maximum test may increase injury risk and a common N-repetition maximum test with several trials is stressful for the patient and in many cases inaccurate, in this paper a model-based approach is proposed for predicting the N-repetition maximum. The individual training intensity represented by the N-repetition maximum is predicted by means of a biomechanical model together with fatigue parameters obtained from an isometric muscle contraction measurement.     

The changing features of the body-mind problem

The body-mind problem invites scientific study, since mental events are repeated and repeatable and invite testable explanations. They seemed troublesome because of the classical theory of substance that failed to solve its own central problems. These are soluble with the aid of the theory of the laws of nature, particularly in its emergentist version [Bunge, M., 1980. The Body-mind Problem, Pergamon, Oxford] that invites refutable explanations [Popper, K.R., 1959. The Logic of Scientific Discovery, Hutchinson, London]. The view of mental properties as emergent is a modification of the two chief classical views, materialism and dualism. As this view invites testable explanations of events of the inner world, it is better than the quasi-behaviorist view of self-awareness as computer-style self-monitoring [Minsky, M., Laske, O., 1992. A conversation with Marvin Minsky. AI Magazine 13 (3), 31-45].     

The application of Markov chain analysis to oligonucleotide frequency prediction and physical mapping of Drosophila melanogaster.

Here we compare several methods for predicting oligonucleotide frequencies in 691 kb of Drosophila melanogaster DNA. As in previous work on Escherichia coli and Saccharomyces cerevisiae, a relatively simple equation based on tetranucleotide frequencies can be used in predicting frequencies of higher order oligonucleotides. For example, the mean of observed/expected abundances of 4,096 hexamers was 1.07 with a sample standard deviation of .55. This simple predictor arises by considering each base on the sense strand of D. melanogaster to depend only on the three bases 5' to it (a 3rd order Markov chain) and is more accurate than the random predictor. This equation is useful in predicting restriction enzyme fragment sizes, selecting restriction enzymes that cut preferentially in coding vs noncoding regions, and in selecting probes to fingerprint clones in contig mapping. Once again, this equation well predicts the occurrence of higher order oligonucleotides, supporting our hypothesis that this predictor holds in evolutionarily diverse organisms. When ranked from highest to lowest abundance, the observed frequencies of oligomers of a given length are closely tracked by the predicted abundances of a 3rd order Markov chain. Through use of the dependence of oligomer frequencies on base composition, we report a list of oligomers that will be useful for the completion of a cosmid physical map of D. melanogaster. Presently, the library is such that it will be possible to construct large contigs using only 30 oligonucleotide probes to fingerprint cosmids.     

Hypothesis testing approaches to the exon prediction problem

MOTIVATION: Many gene identification methods assign scores to gene elements prior to their assembly into predicted genes. The scoring system is often based on log-likelihood ratios. These methods usually perform well but it is difficult to interpret how significant a score is. RESULTS: We have developed several tests of significance for the scores: (1) a sum-of-scores test (SST), (2) an intersection-union test (IUT), based on a multiple hypothesis testing interpretation of an exon's score and (3) a meta-analytical approach (MA), which combines several P-values, corresponding to the exon's parts, to yield a global P-value. We performed simulation studies, which show that the MA has better sensitivity and specificity than other methods and is easier to interpret by non-expert users. This is an improvement over other methods and is especially relevant for users who would like to predict incomplete gene sequences.     

DNA-binding protein prediction using plant specific support vector machines: validation and application of a new genome annotation tool

There are currently 151 plants with draft genomes available but levels of functional annotation for putative protein products are low. Therefore, accurate computational predictions are essential to annotate genomes in the first instance, and to provide focus for the more costly and time consuming functional assays that follow. DNA-binding proteins are an important class of proteins that require annotation, but current computational methods are not applicable for genome wide predictions in plant species. Here, we explore the use of species and lineage specific models for the prediction of DNA-binding proteins in plants. We show that a species specific support vector machine model based on Arabidopsis sequence data is more accurate (accuracy 81%) than a generic model (74%), and based on this we develop a plant specific model for predicting DNA-binding proteins. We apply this model to the tomato proteome and demonstrate its ability to perform accurate high-throughput prediction of DNA-binding proteins. In doing so, we have annotated 36 currently uncharacterised proteins by assigning a putative DNA-binding function. Our model is publically available and we propose it be used in combination with existing tools to help increase annotation levels of DNA-binding proteins encoded in plant genomes.     

Allometry and prediction in hominoids: a solution to the problem of intervening variables.

To avoid misinterpretation of allometric exponents determined from interspecific allometric comparisons, specific conditions must be met with respect to the common reference variable. Body weight is considered to be the best general indication of overall size and is hence widely acknowledged to be the most suitable reference variable. However, because of the paucity of recorded body weights for museum specimens, various comparative studies have used other size indicators as intervening variables, although the allometric relationships to body size/weight were often unknown and possibly differed between species. Because of differences in the scaling properties of alternative intervening variables across the species investigated, conflicting conclusions may be drawn if different variables are chosen as substitutes for overall size. This is illustrated with two examples. In this study, series of skeletons with associated body weights of Gorilla, Pan, Pongo, and Homo were investigated. Both ontogenetic and static adult allometric relationships between several widely used reference variables and body weight were determined. Neither these variables nor additional estimators investigated in this study displayed allometric exponents and coefficients similar enough across species to justify direct interspecific comparison. To generate an alternative size estimator for both ontogenetic and static interspecific investigations, equations for combined sexes were derived to predict body weight from various long bone dimensions for individual hominoid species. From a total of 25 predictors, 12 prediction equations per species (six for nonadults and six for adults) were selected according to their relative suitability for reliable prediction of body weight. It is shown that the derived reference variable "predicted body weight" avoids problems of intervening variables, is valid for any interspecific ontogenetic and static allometric comparison, and displays less fluctuation in comparison to actual body weight.     

PLMLA: prediction of lysine methylation and lysine acetylation by combining multiple features

Post-translational lysine methylation and acetylation are two major modifications of lysine residues. They play critical roles in various biological processes, especially in gene regulation. Identification of protein methylation and acetylation sites would be a foundation for understanding their modification dynamics and molecular mechanism. This work presents a method called PLMLA that incorporates protein sequence information, secondary structure and amino acid properties to predict methylation and acetylation of lysine residues in whole protein sequences. We apply an encoding scheme based on grouped weight and position weight amino acid composition to extract sequence information and physicochemical properties around lysine sites. The prediction accuracy for methyllysine and acetyllysine are 83.02% and 83.08%, respectively. Feature analysis reveals that methyllysine is likely to occur at the coil region and acetyllysine prefers to occur at the helix region of protein. The upstream residues away from the central site may be close to methylated lysine in three-dimensional structure and have a significant influence on methyllysine, while the positively charged residues may have a significant influence on acetyllysine. The online service is available at http://bioinfo.ncu.edu.cn/inquiries_PLMLA.aspx.     

The problem of prediction in invasion biology

Invasion biology is a relatively young discipline which is important, interesting and currently in turmoil. Biological invaders can threaten native ecosystems and global biodiversity; they can incur massive economic costs and even introduce diseases. Invasion biologists generally agree that being able to predict when and where an invasion will occur is essential for progress in their field. However, successful predictions of this type remain elusive. This has caused a rift, as some researchers are pessimistic and believe that invasion biology has no future, whereas others are more optimistic and believe that the key to successful prediction is the creation of a general, unified theoretical framework which encompasses all invasion events. Although I agree that there is a future for invasion biology, extensive synthesis is not the way to better predictions. I argue that the causes of invasion phenomena are exceedingly complex and heterogeneous, hence it is impossible to make generalizations over particular events without sacrificing causal detail. However, this causal detail is just what is needed for the specific predictions which the scientists wish to produce. Instead, I show that a limited type of synthesis (integration of data and methods) is a more useful tool for generating successful predictions. An important implication of my view is that it points to a more pluralistic approach to invasion biology, where generalization and prediction are treated as important yet distinct research goals.     

Fold and function of the InlB B-repeat

Host cell invasion by the facultative intracellular pathogen Listeria monocytogenes requires the invasion protein InlB in many cell types. InlB consists of an N-terminal internalin domain that binds the host cell receptor tyrosine kinase Met and C-terminal GW domains that bind to glycosaminoglycans (GAGs). Met binding and activation is required for host cell invasion, while the interaction between GW domains and GAGs enhances this effect. Soluble InlB elicits the same cellular phenotypes as the natural Met ligand hepatocyte growth factor/scatter factor (HGF/SF), e.g. cell scatter. So far, little is known about the central part of InlB, the B-repeat. Here we present a structural and functional characterization of the InlB B-repeat. The crystal structure reveals a variation of the β-grasp fold that is most similar to small ubiquitin-like modifiers (SUMOs). However, structural similarity also suggests a potential evolutionary relation to bacterial mucin-binding proteins. The B-repeat defines the prototype structure of a hitherto uncharacterized domain present in over a thousand bacterial proteins. Generally, this domain probably acts as a spacer or a receptor-binding domain in extracellular multi-domain proteins. In cellular assays the B-repeat acts synergistically with the internalin domain conferring to it the ability to stimulate cell motility. Thus, the B-repeat probably binds a further host cell receptor and thereby enhances signaling downstream of Met.     

A simple physical model for the prediction and design of protein-DNA interactions

Protein-DNA interactions are crucial for many biological processes. Attempts to model these interactions have generally taken the form of amino acid-base recognition codes or purely sequence-based profile methods, which depend on the availability of extensive sequence and structural information for specific structural families, neglect side-chain conformational variability, and lack generality beyond the structural family used to train the model. Here, we take advantage of recent advances in rotamer-based protein design and the large number of structurally characterized protein-DNA complexes to develop and parameterize a simple physical model for protein-DNA interactions. The model shows considerable promise for redesigning amino acids at protein-DNA interfaces, as design calculations recover the amino acid residue identities and conformations at these interfaces with accuracies comparable to sequence recovery in globular proteins. The model shows promise also for predicting DNA-binding specificity for fixed protein sequences: native DNA sequences are selected correctly from pools of competing DNA substrates; however, incorporation of backbone movement will likely be required to improve performance in homology modeling applications. Interestingly, optimization of zinc finger protein amino acid sequences for high-affinity binding to specific DNA sequences results in proteins with little or no predicted specificity, suggesting that naturally occurring DNA-binding proteins are optimized for specificity rather than affinity. When combined with algorithms that optimize specificity directly, the simple computational model developed here should be useful for the engineering of proteins with novel DNA-binding specificities.     

Haploid evolutionary constructor: new features and further challenges

In this paper we consider the recent advances in methodology for modeling of prokaryotic communities evolution and new features of the software package "Haploid evolutionary constructor" (http://evol-constructor.bionet.nsc.ru). We show the principles of building complex computer models in our software tool. These models describe several levels of biological organization: genetic, metabolic, population, ecological. New features of the haploid evolutionary constructor include the modeling of gene networks and phage infections.     

Structural class prediction: an application of residue distribution along the sequence

Deciphering the native conformation of proteins from their amino acid sequences is one of the most challenging problems in molecular biology. Information on the secondary structure of a protein can be helpful in understanding its native folded state. In our earlier work on molecular chaperones, we have analyzed the hydrophobic and charged patches, short-, medium- and long-range contacts and residue distributions along the sequence. In this article, we have made an attempt to predict the structural class of globular and chaperone proteins based on the information obtained from residue distributions. This method predicts the structural class with an accuracy of 93 and 96%, respectively, for the four- and three-state models in a training set of 120 globular proteins, and 90 and 96%, respectively, for a test set of 80 proteins. We have used this information and methodology to predict the structural classes of chaperones. Interestingly most of the chaperone proteins are predicted under alpha/beta or mixed folding type.     

Conformational properties of deltorphin: new features of the delta-opioid receptor

Deltorphin is an opioid peptide with the sequence H-Tyr-D-Met-Phe-His-Leu-Met-Asp-NH2, recently isolated from the skin of Phyllomedusa sauvagei. Its enormous selectivity towards the delta-opioid receptor and the similarity of the N-terminal part of the sequence with that of dermorphin (H-Tyr-D-Ala-Phe-Gly-Tyr-Pro-Ser-NH2), a mu selective peptide isolated from the same natural source, prompted a comparative conformational study. A 1H-NMR study in two different solvent systems showed that the conformational preferences of the N-terminal sequences of the two peptides are similar. The different selectivities towards opioid receptors have been interpreted in terms of charge effects. Besides a general trend consistent with the role of the membrane in the preselection of the peptides, the present study demonstrates the crucial role played by charged residues in the interaction inside the receptors.