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PubMed2001

The declarative/procedural model of lexicon and grammar.

Our use of language depends upon two capacities: a mental lexicon of memorized words and a mental grammar of rules that underlie the sequential and hierarchical composition of lexical forms into predictably structured larger words, phrases, and sentences. The declarative/procedural model posits that the lexicon/grammar distinction in language is tied to the distinction between two well-studied brain memory systems. On this view, the memorization and use of at least simple words (those with noncompositional, that is, arbitrary form-meaning pairings) depends upon an associative memory of distributed representations that is subserved by temporal-lobe circuits previously implicated in the learning and use of fact and event knowledge. This "declarative memory" system appears to be specialized for learning arbitrarily related information (i.e., for associative binding). In contrast, the acquisition and use of grammatical rules that underlie symbol manipulation is subserved by frontal/basal-ganglia circuits previously implicated in the implicit (nonconscious) learning and expression of motor and cognitive "skills" and "habits" (e.g., from simple motor acts to skilled game playing). This "procedural" system may be specialized for computing sequences. This novel view of lexicon and grammar offers an alternative to the two main competing theoretical frameworks. It shares the perspective of traditional dual-mechanism theories in positing that the mental lexicon and a symbol-manipulating mental grammar are subserved by distinct computational components that may be linked to distinct brain structures. However, it diverges from these theories where they assume components dedicated to each of the two language capacities (that is, domain-specific) and in their common assumption that lexical memory is a rote list of items. Conversely, while it shares with single-mechanism theories the perspective that the two capacities are subserved by domain-independent computational mechanisms, it diverges from them where they link both capacities to a single associative memory system with broad anatomic distribution. The declarative/procedural model, but neither traditional dual- nor single-mechanism models, predicts double dissociations between lexicon and grammar, with associations among associative memory properties, memorized words and facts, and temporal-lobe structures, and among symbol-manipulation properties, grammatical rule products, motor skills, and frontal/basal-ganglia structures. In order to contrast lexicon and grammar while holding other factors constant, we have focused our investigations of the declarative/procedural model on morphologically complex word forms. Morphological transformations that are (largely) unproductive (e.g., in go-went, solemn-solemnity) are hypothesized to depend upon declarative memory. These have been contrasted with morphological transformations that are fully productive (e.g., in walk-walked, happy-happiness), whose computation is posited to be solely dependent upon grammatical rules subserved by the procedural system. Here evidence is presented from studies that use a range of psycholinguistic and neurolinguistic approaches with children and adults. It is argued that converging evidence from these studies supports the declarative/procedural model of lexicon and grammar.

Aphasia↗
PubMed2006

A state-specific polarizable continuum model time dependent density functional theory method for excited state calculations in solution.

An effective state specific (SS) model for the inclusion of solvent effects in time dependent density functional theory (TD-DFT) computations of excited electronic states has been developed and coded in the framework of the so-called polarizable continuum model (PCM). Different relaxation time regimes can be treated thus giving access to a number of different spectroscopic properties together with solvent relaxation energies of paramount relevance in electron transfer processes. SS and conventional linear response (LR) models have been compared for two benchmark systems (coumarin 153 and formaldehyde in different solvents) and in the limiting simple case of a dipolar solute embedded in a spherical cavity. The results point out the complementarity of LR and SS approaches and the advantages of the latter model especially for polar solvents. The favorable scaling properties of PCM-TD-DFT models in both SS and LR variants and their availability in effective quantum mechanical codes pave the route for the computation of reliable spectroscopic properties of large molecules of technological and/or biological interest in their natural environments.

Biophysics↗
PubMed2006

I-conotoxin superfamily revisited.

The I-conotoxin superfamily (I-Ctx) is known to have four disulfide bonds with the cysteine arrangement C-C-CC-CC-C-C, and the members inhibit or modify ion channels of nerve cells. Recently, Olivera and co-workers (FEBS J. 2005; 272: 4178-4188) have suggested that the previously described I-Ctx should now be divided into two different gene superfamilies, namely, I1 and I2, in view of their having two different types of signal peptides and exhibiting distinct functions. We have revisited the 28 entries presently grouped as I-Ctx in UniProt Swiss-Prot knowledgebase, and on the basis of in silico analysis have divided them into I1 and I2 superfamilies. The sequence analysis has provided a framework for in silico annotation enabling us to carry out computer-based functional characterization of the UniProtKB/TrEMBL entry Q59AA4 from Conus miles and to predict it as a member of the I2 superfamily. Furthermore, we have predicted the mature toxin of this entry and have proposed that it may be an inhibitor of voltage-gated potassium channels.

Amino Acid Sequence↗
PubMed2006

Estimation of genetic and environmental factors for melanoma onset using population-based family data.

Estimation of genetic and environmental contributions to cancers falls in the framework of generalized linear mixed modelling with several random effect components. Computational challenges remain, however, in dealing with binary or survival phenotypes. In this paper, we consider the analysis of melanoma onset in a population of 2.6 million nuclear families in Sweden, for which none of the current survival-based methodologies is feasible. We treat the disease outcome as a binary phenotype, so that the standard proportional hazard model leads to a generalized linear model with the complementary-log link function. For rare diseases this link is very close to the probit link, and thus allows the use of marginal likelihood for the estimation of the variance components. We correct for the survival length bias by censoring the parent generation within each family at the time they attain the same cumulative hazard as the child generation, thus improving the validity of the estimates. Our finding that childhood shared environment in addition to genetic factors had a considerable effect on the development of melanoma is consistent with epidemiological studies.

Adolescent↗
PubMed1993

Relative risk, risk difference and rate difference models for sparse stratified data: a pseudo likelihood approach.

We consider a relative risk and a risk difference model for binomial data, and a rate difference model for Poisson (person year) data. It is assumed that the data are stratified in a large number of small strata. If each stratum has its own parameter in the model, then, due to the large number of parameters, straightforward maximum likelihood leads to inconsistent estimates of the relevant parameters. By contrast to the logistic model, conditioning on the number of events per stratum does not help in eliminating the stratum nuisance parameters. We propose a pseudo likelihood method to overcome these consistency problems. The resulting pseudo maximum likelihood estimates can easily be computed with standard statistical software. Our approach gives a more general framework for the Mantel-Haenszel type estimators proposed in the literature. In the special case of a series of 2 x 2 tables, for the risk and rate difference models, our approach yields exactly these ad hoc Mantel-Haenszel estimators, while for the relative risk model it gives a close approximation of the Mantel-Haenszel relative risk estimator. For the regression models corresponding to the association measures relative risk, risk difference and rate difference, our method provides analogues of conditional logistic regression, which were not previously available.

Analysis of Variance↗
PubMed1982

Necessary and sufficient conditions for Von Kries chromatic adaptation to give color constancy.

Necessary and sufficient spectral conditions are presented for Von Kries chromatic adaptation to give color constancy. Von-Kries-invariant reflectance spectra are computed for illuminant spectral power distributions that are arbitrary linear combinations of the first three daylight phases. Experiments are suggested to test models of color constancy using computed spectra (either exact or approximate) within the illuminant-invariant framework.

Color↗
PubMed2004

Combined compression and elongation experiments and non-linear modelling of liver tissue for surgical simulation.

Uniaxial stress-strain data were obtained from in vitro experiments on 20 porcine livers for compressions, elongations and cycles of compression and then elongation. There were about 70 cylindrical samples, with diameter 7mm and varying height (4-11 mm). The combined compression and elongation test provide a unified framework for both compression and elongation for applications such as computer-aided surgical simulation. It enable the zero stress state of the experimental liver sample to be precisely determined. A new equation that combined both logarithmic and polynomial strain energy forms was proposed in modelling these experimental data. The assumption of incompressibility was justified from a preliminary Poisson's ratio for elongation and compression at 0.43+/-0.16 and 0.47+/-0.15, respectively. This equation provided a good fit for the observed mechanical properties of liver during compression-elongation cycles and for separate compressions or elongations. The root mean square errors were 91.92+/-17.43 Pa, 57.55+/-13.23 Pa and 29.78+/-17.67 Pa, respectively. In comparison with existing strain energy functions, this combined model was the better constitutive equation. Application of this theoretical model to small liver samples and other tissues demonstrated its suitability as the material model of choice for soft tissue.

Animals↗
PubMed2005

A baseline-free procedure for transformation models under interval censorship.

An important property of Cox regression model is that the estimation of regression parameters using the partial likelihood procedure does not depend on its baseline survival function. We call such a procedure baseline-free. Using marginal likelihood, we show that an baseline-free procedure can be derived for a class of general transformation models under interval censoring framework. The baseline-free procedure results a simplified and stable computation algorithm for some complicated and important semiparametric models, such as frailty models and heteroscedastic hazard/rank regression models, where the estimation procedures so far available involve estimation of the infinite dimensional baseline function. A detailed computational algorithm using Markov Chain Monte Carlo stochastic approximation is presented. The proposed procedure is demonstrated through extensive simulation studies, showing the validity of asymptotic consistency and normality. We also illustrate the procedure with a real data set from a study of breast cancer. A heuristic argument showing that the score function is a mean zero martingale is provided.

Algorithms↗
PubMed2005

Predicting oligomeric assemblies: N-mers a primer.

Multi-protein complexes play key roles in many biological processes. However, since the structures of these assemblies are hard to resolve experimentally, the detailed mechanism of how they work cooperatively in the cell has remained elusive. Similarly, recent advances on in silico prediction of protein-protein interactions have so far avoided this difficult problem. In this paper, we present a general algorithm to predict molecular assemblies of homo-oligomers. Given the number of N-mers and the 3D structure of one monomer, the method samples all the possible symmetries that N-mers can be assembled. Based on a scoring function that clusters the low free energy structures at each binding interface, the algorithm predicts the complex structure as well as the symmetry of the protein assembly. The method is quite general and does not involve any free parameters. The algorithm has been implemented as a public server and integrated to the protein-protein complex prediction server ClusPro. Using this application, we validated predictions for trimers, tetramers (discriminating between dimer of dimers and 4-fold symmetry structures), pentamers and hexamers (discriminating between trimer of dimers, dimer of trimers, and 6-fold symmetry structures), for a total of 107 assemblies. For 85% of the multimers, the server predicts the complex structure within an average rms deviation of 2A from the full crystal. For complexes that involve more than one binding interface, the cluster size at each surface provides a strong indication as to which interface forms first. With improving scoring functions and computer power, our multimer docking approach could be used as a framework to address the more general problem of multi-protein assemblies.

Algorithms↗
PubMed2005

4D deformable models with temporal constraints: application to 4D cardiac image segmentation.

Segmentation of time series of 3D cardiac images is clinically used for the assessment of the mechanical function of the left ventricle. To take into account the 4D (3D+T) nature of those images, we propose to extend the deformable surface framework by introducing time-dependent constraints. Thus, in addition to computing an internal force for enforcing the regularity of the deformable model, prior motion knowledge is introduced in the deformation process through either temporal smoothing or trajectory constraints. In this paper, deformable surfaces are represented as simplex meshes owing to their generality and their ability to compute mean curvature at each vertex. The segmentation accuracy of this 4D deformable model is estimated on synthetic SPECT image sequences for which a ground truth about the LV volume is known. Segmentation of non-synthetic SPECT and other modalities 4D images is also discussed.

Heart↗
PubMed1997

A molecular dynamics study of Fe2S2 putidaredoxin: multiple conformations of the C-terminal region.

Putidaredoxin (Pdx) plays an essential role as an electron donor and effector in the biochemical cycle involving cytochrome P450cam. Only recently has an NMR-derived structure for this protein been published, but because of the presence of a paramagnetic Fe2S2 center, the NMR assignment could not be completed for residues within a region of 8 A around the active site. That region was modeled by homology with a related protein. The structural refinement for those experiments was done in vacuum, without the use of electrostatic terms in the force field. The present manuscript will describe and discuss a series of long-time, unrestrained, solution molecular dynamic runs for this system. Results will be presented that construct a molecular-level picture that rationalizes experimental results concerning the conformation and mobility of the C-terminal residue Trp106. At least two different conformers are found for this residue during the simulations. The time scale for interconversion between them is found to be in the subnanosecond regime. The results presented here open the possibility for studying binding and electron transfer between Pdx and P450cam, in a framework that allows for dynamical information to be used during the computational process, instead of the single structures deposited on the protein data base.

Camphor 5-Monooxygenase↗
PubMed2001

Neural computations that underlie decisions about sensory stimuli.

Decision-making behavior has been studied extensively, but the neurophysiological mechanisms responsible for this remarkable cognitive ability are just beginning to be understood. Here we propose neural computations that can account for the formation of categorical decisions about sensory stimuli by accumulating information over time into a single quantity: the logarithm of the likelihood ratio favoring one alternative over another. We also review electrophysio-logical studies that have identified brain structures that may be involved in computing this sort of decision variable. The ideas presented constitute a framework for understanding how and where perceptual decisions are formed in the brain.

Journal Article↗
PubMedDate not supplied

Structural features of toxic chemicals for specific toxicity.

We have studied the structural features of toxic chemicals from the RTECS database associated with specific toxicity. The frameworks, functional groups, and structure patterns of molecules are taken into account. Potential active frameworks, groups, and structure patterns for specific toxicity are gained by computational chemistry approaches. These structural features of toxic chemicals will be helpful in understanding activities of toxic chemicals and useful in predicting the toxicity of chemicals, especially in the early stage of drug design.

Database Management Systems↗
PubMed2005

Maya blue: a computational and spectroscopic study.

Maya Blue pigment, used in pre-Colombian America by the ancient Mayas, is a complex between the clay palygorskite and the indigo dye. The pigment can be manufactured by mixing palygorskite and indigo and heating to T > 120 degrees C. The most quoted hypothesis states that the dye molecules enter the microchannels which permeate the clay structure, thus creating a stable complex. Maya Blue shows a remarkable chemical stability, presumably caused by interactions formed between indigo and clay surfaces. This work aims at studying the nature of these interactions by means of computational and spectroscopic techniques. The encapsulation of indigo inside the clay framework was tested by means of molecular modeling techniques. The calculation of the reaction energies confirmed that the formation of the clay-organic complex can occur only if palygorskite is heated at temperatures well above the water desorption step, when the release of water is entropically favored. H-bonds between the clay framework and the indigo were detected by means of spectroscopic methods. FTIR spectroscopy on outgassed palygorskite and freshly synthesized Maya Blue samples showed that the presence of indigo modifies the spectroscopic features of both structural and zeolitic water, although no clear bands of the dye groups could be observed, presumably due to its very low concentration. The positions and intensities of delta(H2O) and nu(H2O) modes showed that part of the structural water molecules interact via a hydrogen bond with the C=O or N-H groups of indigo. Micro-Raman spectra clearly evidenced the presence of indigo both in original and in freshly synthesized Maya Blue. The nu(C=O) symmetric mode of Maya Blue red-shifts with respect to pure indigo, as the result of the formation of H-bonds with the nearest clay structural water. Ab initio quantum methods were applied on the indigo molecule, both isolated and linked through H-bonds with water, to calculate the magnitude of the expected vibrational shifts. Calculated and experimental vibrational shifts appeared to be in good agreement. The presence of a peak at 17.8 ppm and the shift of the N-H signal in the 1H MAS NMR spectrum of Maya Blue provide evidence of hydrogen bond interactions between indigo and palygorskite in agreement with IR and ab initio methods.

Journal Article↗
PubMed2004

Propagators for the time-dependent Kohn-Sham equations.

In this paper we address the problem of the numerical integration of the time-dependent Schrodinger equation i partial differential (t)phi=Hphi. In particular, we are concerned with the important case where H is the self-consistent Kohn-Sham Hamiltonian that stems from time-dependent functional theory. As the Kohn-Sham potential depends parametrically on the time-dependent density, H is in general time dependent, even in the absence of an external time-dependent field. The present analysis also holds for the description of the excited state dynamics of a many-electron system under the influence of arbitrary external time-dependent electromagnetic fields. Our discussion is separated in two parts: (i) First, we look at several algorithms to approximate exp(A), where A is a time-independent operator [e.g., A=-iDeltatH(tau) for some given time tau]. In particular, polynomial expansions, projection in Krylov subspaces, and split-operator methods are investigated. (ii) We then discuss different approximations for the time-evolution operator, such as the midpoint and implicit rules, and Magnus expansions. Split-operator techniques can also be modified to approximate the full time-dependent propagator. As the Hamiltonian is time dependent, problem (ii) is not equivalent to (i). All these techniques have been implemented and tested in our computer code OCTOPUS, but can be of general use in other frameworks and implementations.

Journal Article↗
PubMed2006

A "partitioned leaping" approach for multiscale modeling of chemical reaction dynamics.

We present a novel multiscale simulation approach for modeling stochasticity in chemical reaction networks. The approach seamlessly integrates exact-stochastic and "leaping" methodologies into a single partitioned leaping algorithmic framework. The technique correctly accounts for stochastic noise at significantly reduced computational cost, requires the definition of only three model-independent parameters, and is particularly well suited for simulating systems containing widely disparate species populations. We present the theoretical foundations of partitioned leaping, discuss various options for its practical implementation, and demonstrate the utility of the method via illustrative examples.

Computer Simulation↗
PubMed2026

Reducing haystacks to needles - ViralClust: A Nextflow pipeline to cluster viral sequences.

BACKGROUND: The rapid accumulation of viral genome sequences presents major challenges for downstream analysis tools, including tools for multiple sequence alignments, phylogeny, and genome/alignment visualization, due to computational constraints and sampling biases caused by outbreak-driven over-representation. Selecting representative genomes through clustering offers a principled alternative to random subsampling, yet choosing appropriate clustering strategies remains non-trivial and context-dependent. RESULTS: Here, we present ViralClust, a modular Nextflow pipeline for bias-aware representative selection from large viral genome datasets. ViralClust integrates five distinct clustering algorithms (CD-HIT-EST, SUMACLUST, VSEARCH, MMSeqs2, and HDBSCAN) within a unified workflow, enabling direct comparison of clustering outcomes and flexible adaptation to diverse biological questions, considering a balanced phylogenetic distribution of the selected sequences. We evaluated ViralClust on six RNA and DNA virus datasets ranging from 632 to 156,586 sequences and spanning genome lengths from 890 to 197,185 nucleotides. Across all datasets, clustering reduced dataset size by ~95 % or more while preserving genetic diversity across species, genera, and families, and effectively mitigating biases introduced by outbreaks, partial genomes, and sequence orientation artifacts. CONCLUSIONS: By supporting whole-genome clustering and scalable representative selection, ViralClust enables efficient and reproducible downstream analyses that would otherwise be computationally infeasible. Rather than offering a prescriptive, guided analysis engine, our framework functions as a flexible comparative collection of complementary strategies, allowing users to empirically evaluate trade-offs and choose the ideal method tailored to their specific analytical endpoints.

Bioinformatics↗
PubMed2006

Statistical mechanics of histories: a cluster Monte Carlo algorithm.

We present an efficient computational approach to sample the histories of nonlinear stochastic processes. This framework builds upon recent work on casting a d-dimensional stochastic dynamical system into a (d+1)-dimensional equilibrium system using the path-integral approach. We introduce a cluster algorithm that efficiently samples histories and discuss how to include measurements that are available into the estimate of the histories. This allows our approach to be applicable to the simulation of rare events and to optimal state and parameter estimation. We demonstrate the utility of this approach for Phi4 Langevin dynamics in two spatial dimensions where our algorithm improves sampling efficiency up to an order of magnitude.

Journal Article↗