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PubMed1993

Microcomputer-assisted kinetic modeling of mammalian gene expression.

New software for microcomputers enables predictive, quantitative models of genetic systems to be produced that can account for the elements of time, scale, and feedback control of hierarchical systems. The flow of genetic information during protein synthesis can be addressed by treating each intermediate as a kinetic element in a linked series of reactions. When the rate of transcription changes, the time required to achieve a new level of the encoded protein is expected to be a function of the conversion rates or half-lives of all intermediates. Kinetic modeling may be used to make predictions and integrate primary data concerning rates of transcription, nuclear mRNA dynamics, nucleocytoplasmic transport, translational control, and other processes that govern the rate of synthesis for specific proteins.

Animals↗
PubMed1989

A model for collicular efferent mechanisms underlying the generation of saccades.

A quantitative model for the generation of saccades is presented which is based on the accepted notion that saccade metrics are coded in the deeper layers of the superior colliculus by the population of recruited movement-related cells. The model has important features derived from electrophysiological data in the monkey: a nonhomogeneous and anisotropic afferent-mapping function relating the outside visual world to collicular coordinates and a dome-shaped activity profile in the deeper layers describing the spatial extent of the recruited movement-related cell population. It is proposed that each cell generates a small movement contribution which is determined both by the neuron's location in the collicular map and its firing rate. The individual cell contributions are then added vectorially to yield the total saccade. The model can generate saccades to single visual stimuli in all directions and simulate electrical stimulation experiments. To account for some nonlinear properties of the saccadic system in the computation of saccade metrics, a nonlinear version of the linear summation model is discussed.

Efferent Pathways↗
PubMed1982

Identification of nonlinear controls in a developmental model of motor speech in hearing and deaf children.

A simple quantitative model for speech development is proposed. The model is developed from observations of two systems, one that of normal hearing children and the other that of those who suffer from congenital profound deafness. Comparison of the two systems provides clues to the type of controls needed to produce normal speech. The possible nonlinear controls which may be used during the development of both the suprasegmental and segmental aspects of speech are identified. The linguistic components of speech are ignored. The interdependence of perceptual systems during developmental phases is taken into account and the importance of the associative cortex in speech-motor control is formulated. Deaf persons may employ the tactile system in developing speech; the distinctive unit of code is called a tacheme.

Cerebral Cortex↗
PubMed1982

A management science approach to contingency models of organizational structure.

This study demonstrates the applicability of a quantitative modeling approach, specifically goal programming, in operationalizing the relationship between environmental variables and specific organizational structural variables for optimal goal attainment. A goal programming model is developed to analyze and determine the optimal relationships for goal attainment.

Analysis of Variance↗
PubMed2026

Quantitative molecular cartography of emergency myelopoiesis reveals conserved modules of hematopoietic activation.

Hematopoietic stem and progenitor cells (HSPCs) respond to infections, inflammation, and regenerative challenges using emergency myelopoiesis (EM) pathways to amplify myeloid cell production. However, it remains unclear how various EM inducers regulate HSPCs using shared or distinct molecular mechanisms. Here, we generate a comprehensive and generalizable cell annotation method (HemaScribe) and a refined quantitative model of hematopoietic differentiation (HemaScape) using single-cell RNA sequencing (scRNA-seq) of murine HSPCs, which we apply to a broad range of EM modalities. We uncover multiple strategies for enhancing myelopoiesis that act at different levels of the HSPC hierarchy and are associated with both unique and shared transcriptional response modules. In particular, we identify a myeloid progenitor-based EM activation module across diverse inflammatory challenges that is conserved in humans and informs outcomes in adult and pediatric acute myeloid leukemia. Our work illuminates fundamental regulatory mechanisms in hematopoietic regeneration that have direct translational applications in disease contexts.

Animals↗
PubMed2024

Quantitative natural history modeling of HPDL-related disease based on cross-sectional data reveals genotype-phenotype correlations.

PURPOSE: Biallelic HPDL variants have been identified as the cause of a progressive childhood-onset movement disorder, with a broad clinical spectrum from severe neurodevelopmental disorder to juvenile-onset pure hereditary spastic paraplegia type 83. This study aims at delineating the geno- and phenotypic spectra of patients with HPDL-related disease, quantitatively modeling the natural history, and uncovering genotype-phenotype associations. METHODS: A cross-sectional analysis of 90 published and 1 novel case was performed, using a Human-Phenotype-Ontology-based approach. Unsupervised phenotypic clustering was used alongside in silico analyses to identify distinct patient subgroups. RESULTS: The study models the natural history of the HPDL-related disease in a global cohort, clarifying the molecular and phenotypic spectrum and identifying 3 distinct subgroups characterized by differences in onset, clinical trajectories, and survival. It establishes genotype-phenotype associations, showing that the presence of moderately pathogenic missense variants in 1 allele leads to a milder, spastic paraplegic phenotype with later disease onset, whereas biallelic, highly pathogenic missense or truncating variants are associated with a more severe phenotype and reduced life span. CONCLUSION: Quantitative and unbiased natural history modeling in HPDL-related disease reveals significant genotype-phenotype associations, providing a foundation for variant interpretation, anticipatory guidance, and choice of outcome measures in future prospective and functional studies.

Humans↗
PubMed1994

A pleiotropic nonadditive model of variation in quantitative traits.

A model of mutation-selection-drift balance incorporating pleiotropic and dominance effects of new mutations on quantitative traits and fitness is investigated and used to predict the amount and nature of genetic variation maintained in segregating populations. The model is based on recent information on the joint distribution of mutant effects on bristle traits and fitness in Drosophila melanogaster from experiments on the accumulation of spontaneous and P element-induced mutations. These experiments suggest a leptokurtic distribution of effects with an intermediate correlation between effects on the trait and fitness. Mutants of large effect tend to be partially recessive while those with smaller effect are on average additive, but apparently with very variable gene action. The model is parameterized with two different sets of information derived from P element insertion and spontaneous mutation data, though the latter are not fully known. They differ in the number of mutations per generation which is assumed to affect the trait. Predictions of the variance maintained for bristle number assuming parameters derived from effects of P element insertions, in which the proportion of mutations with an effect on the trait is small, fit reasonably well with experimental observations. The equilibrium genetic variance is nearly independent of the degree of dominance of new mutations. Heritabilities of between 0.4 and 0.6 are predicted with population sizes from 10(4) to 10(6), and most of the variance for the metric trait in segregating population is due to a small proportion of mutations (about 1% of the total number) with neutral or nearly neutral effects on fitness and intermediate effects on the trait (0.1-0.5 sigma P).(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed2002

Application of non-parametric regression to quantitative structure-activity relationships.

Several non-parametric regressors have been applied to modelling quantitative structure-activity relationship (QSAR) data. Performances were benchmarked against multilinear regression and the nonlinear method of smoothing splines. Variable selection was explored through systematic combinations of different variables and combinations of principal components. For the training set examined--539 inhibitors of the tyrosine kinase, Syk--the best two-descriptor model had a 5-fold cross-validated q2 of 0.43. This was generated by a multi-variate Nadaraya-Watson kernel estimator. A subsequent, independent, test set of 371 similar chemical entities showed the model had some predictive power. Other approaches did not perform as well. A modest increase in predictive ability can be achieved with three descriptors, but the resulting model is less easy to visualise. We conclude that non-parametric regression offers a potentially powerful approach to identifying predictive, low-dimensional QSARs.

Databases, Factual↗
PubMed2000

Nonparametric regression applied to quantitative structure-activity relationships

Several nonparametric regressors have been applied to modeling quantitative structure-activity relationship (QSAR) data. The simplest regressor, the Nadaraya-Watson, was assessed in a genuine multivariate setting. Other regressors, the local linear and the shifted Nadaraya-Watson, were implemented within additive models--a computationally more expedient approach, better suited for low-density designs. Performances were benchmarked against the nonlinear method of smoothing splines. A linear reference point was provided by multilinear regression (MLR). Variable selection was explored using systematic combinations of different variables and combinations of principal components. For the data set examined, 47 inhibitors of dopamine beta-hydroxylase, the additive nonparametric regressors have greater predictive accuracy (as measured by the mean absolute error of the predictions or the Pearson correlation in cross-validation trails) than MLR. The use of principal components did not improve the performance of the nonparametric regressors over use of the original descriptors, since the original descriptors are not strongly correlated. It remains to be seen if the nonparametric regressors can be successfully coupled with better variable selection and dimensionality reduction in the context of high-dimensional QSARs.

Journal Article↗
PubMed2003

High-dimensional model representations generated from low order terms--lp-RS-HDMR.

High-dimensional model representation (HDMR) is a general set of quantitative model assessment and analysis tools for improving the efficiency of deducing high dimensional input-output system behavior. RS-HDMR is a particular form of HDMR based on random sampling (RS) of the input variables. The component functions in an HDMR expansion are optimal choices tailored to the n-variate function f(x) being represented over the desired domain of the n-dimensional vector x. The high-order terms (usually larger than second order, or equivalently beyond cooperativity between pairs of variables) in the expansion are often negligible. When it is necessary to go beyond the first and the second order RS-HDMR, this article introduces a modified low-order term product (lp)-RS-HDMR method to approximately represent the high-order RS-HDMR component functions as products of low-order functions. Using this method the high-order truncated RS-HDMR expansions may be constructed without directly computing the original high-order terms. The mathematical foundations of lp-RS-HDMR are presented along with an illustration of its utility in an atmospheric chemical kinetics model.

Journal Article↗
PubMed2005

Protein linear indices of the 'macromolecular pseudograph alpha-carbon atom adjacency matrix' in bioinformatics. Part 1: prediction of protein stability effects of a complete set of alanine substitutions in Arc repressor.

A novel approach to bio-macromolecular design from a linear algebra point of view is introduced. A protein's total (whole protein) and local (one or more amino acid) linear indices are a new set of bio-macromolecular descriptors of relevance to protein QSAR/QSPR studies. These amino-acid level biochemical descriptors are based on the calculation of linear maps on Rn[f k(xmi):Rn-->Rn] in canonical basis. These bio-macromolecular indices are calculated from the kth power of the macromolecular pseudograph alpha-carbon atom adjacency matrix. Total linear indices are linear functional on Rn. That is, the kth total linear indices are linear maps from Rn to the scalar R[f k(xm):Rn-->R]. Thus, the kth total linear indices are calculated by summing the amino-acid linear indices of all amino acids in the protein molecule. A study of the protein stability effects for a complete set of alanine substitutions in the Arc repressor illustrates this approach. A quantitative model that discriminates near wild-type stability alanine mutants from the reduced-stability ones in a training series was obtained. This model permitted the correct classification of 97.56% (40/41) and 91.67% (11/12) of proteins in the training and test set, respectively. It shows a high Matthews correlation coefficient (MCC=0.952) for the training set and an MCC=0.837 for the external prediction set. Additionally, canonical regression analysis corroborated the statistical quality of the classification model (Rcanc=0.824). This analysis was also used to compute biological stability canonical scores for each Arc alanine mutant. On the other hand, the linear piecewise regression model compared favorably with respect to the linear regression one on predicting the melting temperature (tm) of the Arc alanine mutants. The linear model explains almost 81% of the variance of the experimental tm (R=0.90 and s=4.29) and the LOO press statistics evidenced its predictive ability (q2=0.72 and scv=4.79). Moreover, the TOMOCOMD-CAMPS method produced a linear piecewise regression (R=0.97) between protein backbone descriptors and tm values for alanine mutants of the Arc repressor. A break-point value of 51.87 degrees C characterized two mutant clusters and coincided perfectly with the experimental scale. For this reason, we can use the linear discriminant analysis and piecewise models in combination to classify and predict the stability of the mutant Arc homodimers. These models also permitted the interpretation of the driving forces of such folding process, indicating that topologic/topographic protein backbone interactions control the stability profile of wild-type Arc and its alanine mutants.

Alanine↗
PubMedDate not supplied

A new approach to predict the biological activity of molecules based on similarity of their interaction fields and the logP and logD values: application to auxins.

The activity of a biological compound is dependent both on specific binding to a target receptor and its ADME (Absorption, Distribution, Metabolism, Excretion) properties. A challenge to predict biological activity is to consider both contributions simultaneously in deriving quantitative models. We present a novel approach to derive QSAR models combining similarity analysis of molecular interaction fields (MIFs) with prediction of logP and/or logD. This new classification method is applied to a set of about 100 compounds related to the auxin plant hormone. The classification based on similarity of their interaction fields is more successful for the indole than the phenoxy compounds. The classification of the phenoxy compounds is however improved by taking into account the influence of the logP and/or the logD values on biological activity. With the new combined method, the majority (8 out of 10) of the previously misclassified derivatives of phenoxy acetic acid are classified in accord with their bioassays. The recently determined crystal structure of the auxin-binding protein 1 (ABP1) enabled validation of our approach. The results of docking a few auxin related compounds with different biological activity to ABP1 correlate well with the classification based on similarity of MIFs only. Biological activity is, however, better predicted by a combined similarity of MIFs + logP/logD approach.

Indoleacetic Acids↗
PubMedDate not supplied

Linear indices of the "molecular pseudograph's atom adjacency matrix": definition, significance-interpretation, and application to QSAR analysis of flavone derivatives as HIV-1 integrase inhibitors.

This report describes a new set of molecular descriptors of relevance to QSAR/QSPR studies and drug design, atom linear indices fk(xi). These atomic level chemical descriptors are based on the calculation of linear maps on Rn[fk(xi): Rn--> Rn] in canonical basis. In this context, the kth power of the molecular pseudograph's atom adjacency matrix [Mk(G)] denotes the matrix of fk(xi) with respect to the canonical basis. In addition, a local-fragment (atom-type) formalism was developed. The kth atom-type linear indices are calculated by summing the kth atom linear indices of all atoms of the same atom type in the molecules. Moreover, total (whole-molecule) linear indices are also proposed. This descriptor is a linear functional (linear form) on Rn. That is, the kth total linear indices is a linear map from Rn to the scalar R[ fk(x): Rn --> R]. Thus, the kth total linear indices are calculated by summing the atom linear indices of all atoms in the molecule. The features of the kth total and local linear indices are illustrated by examples of various types of molecular structures, including chain-lengthening, branching, heteroatoms-content, and multiple bonds. Additionally, the linear independence of the local linear indices to other 0D, 1D, 2D, and 3D molecular descriptors is demonstrated by using principal component analysis for 42 very heterogeneous molecules. Much redundancy and overlapping was found among total linear indices and most of the other structural indices presently in use in the QSPR/QSAR practice. On the contrary, the information carried by atom-type linear indices was strikingly different from that codified in most of the 229 0D-3D molecular descriptors used in this study. It is concluded that the local linear indices are an independent indices containing important structural information to be used in QSPR/QSAR and drug design studies. In this sense, atom, atom-type, and total linear indices were used for the prediction of pIC50 values for the cleavage process of a set of flavone derivatives inhibitors of HIV-1 integrase. Quantitative models found are significant from a statistical point of view (R of 0.965, 0.902, and 0.927, respectively) and permit a clear interpretation of the studied properties in terms of the structural features of molecules. A LOO cross-validation procedure revealed that the regression models had a fairly good predictability (q2 of 0.679, 0.543, and 0.721, respectively). The comparison with other approaches reveals good behavior of the method proposed. The approach described in this paper appears to be an excellent alternative or guides for discovery and optimization of new lead compounds.

Computer Simulation↗
PubMed2004

Neurophysiologically-based mean-field modelling of tonic cortical activity in post-traumatic stress disorder (PTSD), schizophrenia, first episode schizophrenia and attention deficit hyperactivity disorder (ADHD).

A recently developed quantitative model of cortical activity is used that permits data comparison with experiment using a quantitative and standardized means. The model incorporates properties of neurophysiology including axonal transmission delays, synaptodendritic rates, range-dependent connectivities, excitatory and inhibitory neural populations, and intrathalamic, intracortical, corticocortical and corticothalamic pathways. This study tests the ability of the model to determine unique physiological properties in a number of different data sets varying in mean age and pathology. The model is used to fit individual electroencephalographic (EEG) spectra from post-traumatic stress disorder (PTSD), schizophrenia, first episode schizophrenia (FESz), attention deficit hyperactivity disorder (ADHD), and their age/sex matched controls. The results demonstrate that the model is able to distinguish each group in terms of a unique cluster of abnormal parameter deviations. The abnormal physiology inferred from these parameters is also consistent with known theoretical and experimental findings from each disorder. The model is also found to be sensitive to the effects of medication in the schizophrenia and FESz group, further supporting the validity of the model.

Adolescent↗
PubMed1992

Development of an in vitro model to study carcinogen-induced neoplastic progression of initiated mouse epidermal cells.

Initiation and promotion in mouse skin carcinogenesis produce multiple benign tumors, squamous papillomas, but only a few squamous cell carcinomas. The spontaneous conversion from the benign to the malignant phenotype occurs over many months and in stages, but induced malignant conversion can be accomplished more rapidly by exposure of papilloma-bearing mice to mutagens or by transfection of papilloma cell lines with specific oncogenes. The analysis of genetic targets responsible for carcinogen-induced neoplastic progression would be facilitated by the development of in vitro models where the process is rapid, focal, and quantitative. To this end, primary newborn mouse keratinocytes were initiated in vitro by the introduction of the v-rasHa oncogene via a defective retrovirus. Recipient cells produce squamous papillomas and have a high proliferation rate in culture medium with 0.05 mM Ca2+, but fail to grow in medium with 0.5 mM Ca2+ which is permissive for growth of malignant keratinocytes. When v-rasHa-keratinocytes were exposed to mutagens in vitro, proliferative foci emerged after culture in 0.5 mM Ca2+ for 4 weeks. These foci stained intensely red with rhodamine stain, could be easily quantitated, and readily incorporated bromodeoxyuridine. Dose-response studies with several mutagens indicated that the number of foci increased with concentration to the point where excessive cytotoxicity developed. Mutagens varied in potency for producing foci in the following order: cis-diamminedichloroplatinum greater than or equal to benzo(a)pyrene diolexpoxide I greater than N-methyl-N'-nitro-N-nitrosoguanidine greater than or equal to 4-nitroquinoline-N-oxide greater than N-acetoxy-acetyl- aminofluorene. The tumor promoter 12-O-tetradecanoylphorbol-13-acetate was inactive in the assay. A subset of cell lines derived from foci produced malignant tumors in vivo, while others were not tumorigenic. Analysis of DNA from cell lines and tumors revealed that most tumorigenic cell lines maintained the v-rasHa genome, whereas the viral sequences were deleted in nontumorigenic cell lines. Immunohistochemical analysis indicated that proliferative foci and quiescent v-rasHa keratinocytes expressed keratin 8, a marker of v-rasHa expression in cultured keratinocytes. Cells in foci, but not v-rasHa control cells, expressed keratin 13, a marker which is strongly associated with the malignant progression of skin tumors in vivo. This in vitro assay provides a quantitative model to study chemically induced focal neoplastic progression at the cellular level and to identify agents which may be selective for enhancing malignant conversion.

Animals↗
PubMed2000

Modeling solid-to-solid biocatalysis: integration of six consecutive steps.

A quantitative model for the conversion of a solid-substrate salt to a solid-product salt in a batch bioreactor seeded with product crystals is presented. The overall process consists of six serial steps (with dissolution and crystallization each in themselves complex multistep processes): solid-salt dissolution, salt dissociation into an ionic substrate and a counter-ion, bioconversion accompanied by biocatalyst inactivation, complexation of the ionic product with the counter-ion, and salt crystal growth. In the model, the consecutive steps are integrated, including biocatalyst inactivation and assuming that salt dissociation and complexation of ions are at equilibrium. Model parameters were determined previously in separate independent experiments. To validate the model, either dissolved or solid Ca-maleate was converted to solid Ca-D-malate by permeabilized Pseudomonas pseudoalcaligenes in a batch bioreactor seeded with Ca-D-malate crystals. The model very well predicted the concentrations of all components in the liquid phase (Ca-maleate, Ca(2+), maleate(2-), D-malate(2-), and Ca-D-malate) and the amounts of the solid phases (Ca-maleate. H(2)O and Ca-D-malate. 3H(2)O), especially when high initial amounts of Ca-maleate. H(2)O and Ca-D-malate. 3H(2)O were present.

Bioreactors↗
PubMed1984

An immune response profile model for immunogenicity quantitation.

We propose an analytical model, which can simultaneously depict many fundamental characteristics of the immunogenicity of various vaccines. This model, the Immune Response (IR) profile, conveniently expresses the mathematical relation between pre- and post-vaccination titers. A vaccine's IR profile is antigen-specific, dose-dependent and post-vaccination interval-dependent. The maximal capability for serological response to a vaccine can be determined using this model irrespective of the dose administered, the post-vaccination assay interval, or the live or killed state of the vaccine. The IR profile obtained from analysis of booster vaccine responses in a limited number of seropositive study subjects can be used to predict maximal antibody titers which are expected after vaccination and can predict the geometric mean post-vaccination antibody titer of a cohort of subjects undergoing primary immunization. Using this model, it is anticipated that the immunoregulation implied by the IR profile may also prove to be correlated with cellular subpopulations and idiotypic antibody functions. Although derived from influenza vaccines analyses, the model successfully describes immune response characteristics following natural infection with malaria and following diphtheria and rubella vaccine administration.

Adolescent↗
PubMed1997

Local control model of excitation-contraction coupling in skeletal muscle.

This is a quantitative model of control of Ca release from the sarcoplasmic reticulum in skeletal muscle, based on dual control of release channels (ryanodine receptors), primarily by voltage, secondarily by Ca (Ríos, E., and G. Pizarro. 1988. 3:223-227). Channels are positioned in a double row array of between 10 and 60 channels, where exactly half face voltage sensors (dihydropyridine receptors) in the transverse (t) tubule membrane (Block, B.A., T. Imagawa, K.P. Campbell, and C. Franzini-Armstrong. 1988. 107:2587-2600). We calculate the flux of Ca release upon different patterns of pulsed t-tubule depolarization by explicit stochastic simulation of the states of all channels in the array. Channels are initially opened by voltage sensors, according to an allosteric prescription (Ríos, E., M. Karhanek, J. Ma, A. González. 1993. 102:449-482). Ca permeating the open channels, diffusing in the junctional gap space, and interacting with fixed and mobile buffers produces defined and changing distributions of Ca concentration. These concentrations interact with activating and inactivating channel sites to determine the propagation of activation and inactivation within the array. The model satisfactorily simulates several whole-cell observations, including kinetics and voltage dependence of release flux, the "paradox of control," whereby Ca-activated release remains under voltage control, and, most surprisingly, the "quantal" aspects of activation and inactivation (Pizarro, G., N. Shirokova, A. Tsugorka, and E. Ríos. 1997. 501:289-303). Additionally, the model produces discrete events of activation that resemble Ca sparks (Cheng, H., M.B. Cannell, and W.J. Lederer. 1993. 262:740-744). All these properties result from the intersection of stochastic channel properties, control by local Ca, and, most importantly, the one dimensional geometry of the array and its mesoscopic scale. Our calculations support the concept that the release channels associated with one face of one junctional t-tubule segment, with its voltage sensor, constitute a functional unit, termed the "couplon." This unit is fundamental: the whole cell behavior can be synthesized as that of a set of couplons, rather than a set of independent channels.

Animals↗