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PubMed1999

A combined approach for ab initio construction of low resolution protein tertiary structures from sequence.

An approach to construct low resolution models of protein structure from sequence information using a combination of different methodologies is described. All possible compact self-avoiding C alpha conformations (approximately 10 million) of a small protein chain were exhaustively enumerated on a tetrahedral lattice. The best scoring 10,000 conformations were selected using a lattice-based scoring function. All-atom structures were then generated by fitting an off-lattice four-state phi/psi model to the lattice conformations, using idealised helix and sheet values based on predicted secondary structure. The all-atom conformations were minimised using ENCAD and scored using a second hybrid scoring function. The best scoring 50, 100, and 500 conformations were input to a consensus-based distance geometry routine that used constraints from each the conformation sets and produced a single structure for each set (total of three). Secondary structures were again fitted to the three structures, and the resulting structures were minimised and scored. The lowest scoring conformation was taken to be the "correct" answer. The results of application of this method to twelve proteins are presented.

Amino Acid Sequence↗
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↗
PubMed2001

Alopex-B: a new, simpler, but yet faster version of the alopex training algorithm.

Experimenting with some changes and simplifications to the Alopex algorithm, we obtained a new faster version (Alopex-B), that also shows lower failure rates on training attempts. Like Alopex, our version is network-architecture independent, does not require error or transfer functions to be differentiable, has a high potential for parallelism, and is stochastic (which helps avoid local minima), but unlike Alopex it follows no annealing scheme, and uses less parameters which makes it simpler to implement and to use.

Algorithms↗
PubMed1997

Invariant object recognition using higher-order neural networks, line-segment spectra and multi-resolution training.

A second-order neural network architecture is introduced that achieves invariant recognition with respect to an object's position and orientation in an image. This network does not show the combinatorial growth in network size as image size is increased, which is commonly observed in higher-order architectures. A new concept called an object's line-segment spectrum is introduced. It is argued that the weights of the second-order architecture are determined by these line-segments. Training time then becomes a function of object size rather than image size. The network is tested on the 26 capital letters of the alphabet. It is shown that in this application a multi-resolution training approach leads to reduced training time and improved performance.

Neural Networks, Computer↗
PubMed2003

Disease genes and intracellular protein networks.

By a computational approach we reconstructed genomic transcriptional profiles of 19 different adult human tissues, based on information on activity of 27,924 genes obtained from unbiased UniGene cDNA libraries. In each considered tissue, a small number of genes resulted highly expressed or "tissue specific." Distribution of gene expression levels in a tissue appears to follow a power law, thus suggesting a correspondence between transcriptional profile and "scale-free" topology of protein networks. The expression of 737 genes involved in Mendelian diseases was analyzed, compared with a large reference set of known human genes. Disease genes resulted significantly more expressed than expected. The possible correspondence of their products to important nodes of intracellular protein network is suggested. Auto-organization of the protein network, its stability in time in the differentiated state, and relationships with the degree of genetic variability at genome level are discussed.

Adult↗
PubMed2003

MRAD: Metabolic reaction analysis database--an entity-relationship approach.

The Metabolic Reaction Analysis Database (MRAD) is a relational database based on the Entity-Relationship (ER) model which combines information about organisms, biochemical pathways, reactions, enzymes, substrates, products and genes. It describes 244,596 genes in 79 organisms, 6,552 enzymes, and 3,552 reactions, 3,100 substrates, 2,866 products and 118 metabolic pathways. The MRAD graphical user interface allows for the identification of metabolic reactions which are similar and dissimilar in multiple organisms, reactions in a pathway which are missing in an organism and using any combination between one to six of the biological entities of organisms, genes, pathways, enzymes, substrates and products to determine metabolic reactions. MRAD provides a powerful and efficient tool for the construction of flux balance models for metabolic engineering applications.

Computer Graphics↗
PubMed2006

Development of bioinformatics resources for display and analysis of copy number and other structural variants in the human genome.

The discovery of an abundance of copy number variants (CNVs; gains and losses of DNA sequences >1 kb) and other structural variants in the human genome is influencing the way research and diagnostic analyses are being designed and interpreted. As such, comprehensive databases with the most relevant information will be critical to fully understand the results and have impact in a diverse range of disciplines ranging from molecular biology to clinical genetics. Here, we describe the development of bioinformatics resources to facilitate these studies. The Database of Genomic Variants (http://projects.tcag.ca/variation/) is a comprehensive catalogue of structural variation in the human genome. The database currently contains 1,267 regions reported to contain copy number variation or inversions in apparently healthy human cases. We describe the current contents of the database and how it can serve as a resource for interpretation of array comparative genomic hybridization (array CGH) and other DNA copy imbalance data. We also present the structure of the database, which was built using a new data modeling methodology termed Cross-Referenced Tables (XRT). This is a generic and easy-to-use platform, which is strong in handling textual data and complex relationships. Web-based presentation tools have been built allowing publication of XRT data to the web immediately along with rapid sharing of files with other databases and genome browsers. We also describe a novel tool named eFISH (electronic fluorescence in situ hybridization) (http://projects.tcag.ca/efish/), a BLAST-based program that was developed to facilitate the choice of appropriate clones for FISH and CGH experiments, as well as interpretation of results in which genomic DNA probes are used in hybridization-based experiments.

Algorithms↗
PubMed1989

Analysis of reciprocal creatinine plots by two-phase linear regression.

The progression of renal diseases is often monitored by the serial measurement of plasma creatinine. The slope of the linear relation that is frequently found between the reciprocal of creatinine concentration and time delineates the rate of change in renal function. Minor changes in slope, perhaps indicating response to therapeutic intervention, can be difficult to identify and yet be of clinical importance. We describe the application of two-phase linear regression to identify and characterise changes in slope using a microcomputer. The method fits two intersecting lines to the data by computing a least-squares estimate of the position of the slope change and its 95% confidence limits. This avoids the potential bias of fixing the change at a preconceived time corresponding with an alteration in treatment. The program then evaluates the statistical and clinical significance of the slope change and produces a graphical output to aid interpretation.

Adult↗
PubMed2002

On the emergence of rules in neural networks.

A simple associationist neural network learns to factor abstract rules (i.e., grammars) from sequences of arbitrary input symbols by inventing abstract representations that accommodate unseen symbol sets as well as unseen but similar grammars. The neural network is shown to have the ability to transfer grammatical knowledge to both new symbol vocabularies and new grammars. Analysis of the state-space shows that the network learns generalized abstract structures of the input and is not simply memorizing the input strings. These representations are context sensitive, hierarchical, and based on the state variable of the finite-state machines that the neural network has learned. Generalization to new symbol sets or grammars arises from the spatial nature of the internal representations used by the network, allowing new symbol sets to be encoded close to symbol sets that have already been learned in the hidden unit space of the network. The results are counter to the arguments that learning algorithms based on weight adaptation after each exemplar presentation (such as the long term potentiation found in the mammalian nervous system) cannot in principle extract symbolic knowledge from positive examples as prescribed by prevailing human linguistic theory and evolutionary psychology.

Algorithms↗
PubMed1999

An approach to biological computation: unicellular core-memory creatures evolved using genetic algorithms.

A novel machine language genetic programming system that uses one-dimensional core memories is proposed and simulated. The core is compared to a biochemical reaction space, and in imitation of biological molecules, four types of data words (Membrane, Pure data, Operator, and Instruction) are prepared in the core. A program is represented by a sequence of Instructions. During execution of the core, Instructions are transcribed into corresponding Operators, and Operators modify, create, or transfer Pure data. The core is hierarchically partitioned into sections by the Membrane data, and the data transfer between sections by special channel Operators constitutes a tree data-flow structure among sections in the core. In the experiment, genetic algorithms are used to modify program information. A simple machine learning problem is prepared for the environment data set of the creatures (programs), and the fitness value of a creature is calculated from the Pure data excreted by the creature. Breeding of programs that can output the predefined answer is successfully carried out. Several future plans to extend this system are also discussed.

Algorithms↗
PubMed2003

AMIDE: a free software tool for multimodality medical image analysis.

Amide's a Medical Image Data Examiner (AMIDE) has been developed as a user-friendly, open-source software tool for displaying and analyzing multimodality volumetric medical images. Central to the package's abilities to simultaneously display multiple data sets (e.g., PET, CT, MRI) and regions of interest is the on-demand data reslicing implemented within the program. Data sets can be freely shifted, rotated, viewed, and analyzed with the program automatically handling interpolation as needed from the original data. Validation has been performed by comparing the output of AMIDE with that of several existing software packages. AMIDE runs on UNIX, Macintosh OS X, and Microsoft Windows platforms, and it is freely available with source code under the terms of the GNU General Public License.

Costs and Cost Analysis↗
PubMed2006

Genetic Parallel Programming: design and implementation.

This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially.

Algorithms↗
PubMed2006

Error thresholds in genetic algorithms.

The error threshold of replication is an important notion in the quasispecies evolution model; it is a critical mutation rate (error rate) beyond which structures obtained by an evolutionary process are destroyed more frequently than selection can reproduce them. With mutation rates above this critical value, an error catastrophe occurs and the genomic information is irretrievably lost. Therefore, studying the factors that alter this magnitude has important implications in the study of evolution. Here we use a genetic algorithm, instead of the quasispecies model, as the underlying model of evolution, and explore whether the phenomenon of error thresholds is found on finite populations of bit strings evolving on complex landscapes. Our empirical results verify the occurrence of error thresholds in genetic algorithms. In this way, this notion is brought from molecular evolution to evolutionary computation. We also study the effect of modifying the most prominent evolutionary parameters on the magnitude of this critical value, and found that error thresholds depend mainly on the selection pressure and genotype length.

Algorithms↗
PubMed2006

GASAT: a genetic local search algorithm for the satisfiability problem.

This paper presents GASAT, a hybrid algorithm for the satisfiability problem (SAT). The main feature of GASAT is that it includes a recombination stage based on a specific crossover and a tabu search stage. We have conducted experiments to evaluate the different components of GASAT and to compare its overall performance with state-of-the-art SAT algorithms. These experiments show that GASAT provides very competitive results.

Algorithms↗
PubMedDate not supplied

Graphic representation of numerically calculated predictive values: an easily comprehended method of evaluating diagnostic tests.

The authors present a brief BASIC-language computer program that calculates positive and negative predictive values from the known sensitivity and specificity of a test over a range of disease prevalences and produces easily comprehended graphs of these relationships using commonly employed graphics software. These graphs permit rapid appreciation of the effect of prior probability on predictive values. They may facilitate selection of the appropriate test for the anticipated setting and avoidance of the unexpected inaccuracies that often result when tests are chosen on the basis of sensitivity and specificity alone.

Computer Graphics↗
PubMed1986

Autistic children grow up: an eight to twenty-four year follow-up study.

Eighty questionnaires were sent to parents and/or caregivers of autistic persons diagnosed between 1960-73 at CPRI, a regional assessment and treatment centre. The objective was to determine their present place of residence, functioning ability, language development, program involvement, and seizure activity. The results of this study support evidence that more than 50 percent require long-term institutional care; almost one-third suffer epileptic seizures; there is a persistence of symptoms and difficulty in gaining useful speech; few live independently or are capable of employment.

Adolescent↗
PubMed1995

An introduction to multivariate adaptive regression splines.

Multivariate Adaptive Regression Splines (MARS) is a method for flexible modelling of high dimensional data. The model takes the form of an expansion in product spline basis functions, where the number of basis functions as well as the parameters associated with each one (product degree and knot locations) are automatically determined by the data. This procedure is motivated by recursive partitioning (e.g. CART) and shares its ability to capture high order interactions. However, it has more power and flexibility to model relationships that are nearly additive or involve interactions in at most a few variables, and produces continuous models with continuous derivatives. In addition, the model can be represented in a form that separately identifies the additive contributions and those associated with different multivariable interactions. This paper summarizes the basic MARS algorithm, as well as extensions for binary response, categorical predictors, nested variables and missing values. It presents tips on interpreting the output of the standard FORTRAN implementation of MARS, and provides an example of MARS applied to a set of clinical data.

Algorithms↗