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At least 325 records · Page 18Linked to original sources
PubMed1983

Acoustic modeling of lung dynamics using bond graphs.

Bond graphs are used to model the acoustic behavior of the respiratory system. The model includes the distributed dynamics of the upper airways while the lower passage generations are represented by "lumping" of resistance and compliance effects. The lower airway representation is terminated with ten lung segments. The model is accurate for frequencies as high as 8500 Hz. The model is currently capable of predicting system eigenvalues as a function of system parameters and geometry for a "nonbreathing" lung. Future plans include modifying the model to include lung segment expansion and contraction as well as turbulence generation at airway bifurcations.

Acoustics↗
PubMed1969

Cell population kinetics: a modified interpretation of the graph of labeled mitoses.

Graphs of labeled mitoses, derived from autoradiographs of cell populations with (3)H-thymidine, show depressions in the curves at their midpoints. These depressions reflect interruption of DNA synthesis midway through S phase. Such interruptions revealed by the method of labeled mitoses should be considered when determining cell-cycle times.

Animals↗
PubMed1988

A graph-dynamic model of the power law of practice and the problem-solving fan-effect.

Numerous human learning phenomena have been observed and captured by individual laws, but no unified theory of learning has succeeded in accounting for these observations. A theory and model are proposed that account for two of these phenomena: the power law of practice and the problem-solving fan-effect. The power law of practice states that the speed of performance of a task will improve as a power of the number of times that the task is performed. The power law resulting from two sorts of problem-solving changes, addition of operators to the problem-space graph and alterations in the decision procedure used to decide which operator to apply at a particular state, is empirically demonstrated. The model provides an analytic account for both of these sources of the power law. The model also predicts a problem-solving fan-effect, slowdown during practice caused by an increase in the difficulty of making useful decisions between possible paths, which is also found empirically.

Decision Making↗
PubMed2000

Identifying amino acid residues in medium resolution critical point graphs using instance based query generation.

Instance Based Query Generation is defined and applied to the problem of recognising amino acid residues in medium resolution critical point graphs. The technique is an amalgamation of Relational Instance Based Learning and Frequent Query Discovery in First Order Logic. Instances are automatically constructed from a deductive database and first order association rules are derived from the instances. The initial investigations presented here indicate that the technique is able to discriminate some of the larger amino acid types as well as discriminating the protein from background solvent. Identification of the smaller amino acids remains difficult and requires further work.

Amino Acids↗
PubMed1999

Spatial analysis of the neuronal density of aminergic brainstem nuclei in primary neurodegenerative and vascular dementia: a comparative immunocytochemical and quantitative study using a graph method.

A graph method was employed to analyse spatial neuronal patterns of pontine nuclei with ascending aminergic projections to the forebrain (nucleus centralis superior (NCS), raphes dorsalis (NRD) and locus coeruleus (LC)), in Alzheimer disease (AD), Huntington disease (HD), and vascular (VD) as well as "mixed-type" (VA) dementia, compared with non-demented controls (CO) and a small sample of brains from schizophrenics ("dementia praecox" (DP)). The quantitative evaluations by the "minimal spanning tree (MST)" were complemented by rough neurofibrillary tangle (NFT) counts and by semiquantitative immunohistochemical assessment of amyloid deposition, neuritic plaque formation, and cellular gliosis. The AD cases showed a significant decline of neuronal density in all nuclei examined, as compared with controls and DP. Neuronal loss was not significant in VD, while the mixed cases with both vascular and Alzheimer-type pathology exhibited pronounced changes of neuronal density. Amyloid deposition occurred almost exclusively in AD and VA, as a rule, being of moderate degree, except for two presenile AD cases where it was marked. NFT were significantly increased in all nuclei in AD and in the VA cases, while they only occasionally appeared beyond age 55 in HD, DP and CO. The four HD cases showed in the NCS and NRD neuronal loss as severe as in AD. This neuronal loss implicates impairment of serotoninergic and noradrenergic neuromodulation as one basic mechanism promoting dementia in AD, VA and perhaps in HD.

Adult↗
PubMed1999

Replicator equations, maximal cliques, and graph isomorphism.

We present a new energy-minimization framework for the graph isomorphism problem that is based on an equivalent maximum clique formulation. The approach is centered around a fundamental result proved by Motzkin and Straus in the mid-1960s, and recently expanded in various ways, which allows us to formulate the maximum clique problem in terms of a standard quadratic program. The attractive feature of this formulation is that a clear one-to-one correspondence exists between the solutions of the quadratic program and those in the original, combinatorial problem. To solve the program we use the so-called replicator equations--a class of straightforward continuous- and discrete-time dynamical systems developed in various branches of theoretical biology. We show how, despite their inherent inability to escape from local solutions, they nevertheless provide experimental results that are competitive with those obtained using more elaborate mean-field annealing heuristics.

Mathematics↗
PubMed1999

Propagating distributions up directed acyclic graphs.

In a previous article, we considered game trees as graphical models. Adopting an evaluation function that returned a probability distribution over values likely to be taken at a given position, we described how to build a model of uncertainty and use it for utility-directed growth of the search tree and for deciding on a move after search was completed. In some games, such as chess and Othello, the same position can occur more than once, collapsing the game tree to a directed acyclic graph (DAG). This induces correlations among the distributions at sibling nodes. This article discusses some issues that arise in extending our algorithms to a DAG. We give a simply described algorithm for correctly propagating distributions up a game DAG, taking account of dependencies induced by the DAG structure. This algorithm is exponential time in the worst case. We prove that it is #P complete to propagate distributions up a game DAG correctly. We suggest how our exact propagation algorithm can yield a fast but inexact heuristic.

Algorithms↗
PubMed1996

Neural network for dynamic binding with graph representation: form, linking, and depth-from-occlusion.

A neural network is presented that explicitly represents form attributes and relations between them, thus solving the binding problem without temporal coding. Rather, the network create a graph representation by dynamically allocating nodes to code local form attributes and establishing arcs to link them. With this representation, the network selectively groups and segments in depth objects based on line junction information, producing results consistent with those of several recent visual search experiments. In addition to depth-from-occlusion, the network provides a sufficient framework for local line-labeling processes to recover other three-dimensional (3-D) variables, such as edge/surface contiguity, edge slant, and edge convexity.

Form Perception↗
PubMed1994

Using self-recording, evaluation, and graphing to increase completion of homework assignments.

This article describes the use of self-monitoring procedures to increase the number of daily homework assignments completed by eight students with learning disabilities. Students ranged in age from 13 to 16 years and attended Grades 7 through 10. The experimental procedure involved the use of a sheet listing all daily assignments given by regular classroom teachers. A multiple-baseline design across subjects demonstrated a clear relationship between the introduction of self-monitoring of assignments and an increase in assignments completed. Goal setting and self-graphing of data appeared to increase this effect.

Adolescent↗
PubMed2000

Prediction of angiographic stabilization/regression of coronary atherosclerosis by a risk factor graph.

BACKGROUND: The only reason for treating dyslipidaemia is the prevention and/or stabilization of atherosclerosis. Angiographic stabilization/reversal of coronary atherosclerosis predicts a decrease in future atherosclerotic disease manifestations. METHODS: This paper reports on an analysis of eight angiographic trials that use therapy of dyslipidaemia in order to stabilize/reverse coronary atherosclerosis. The analysis involved plotting trial lipid and blood pressure end-points on a risk factor graph which contained a threshold line in order to determine whether bringing trial end-points below that threshold line predicted angiographic stabilization/regression of coronary atherosclerosis. RESULTS: In fact, the angiograms for those patients whose lipid-blood pressure plots were brought below the threshold line exhibited stabilization/regression of coronary atherosclerosis in 75% of cases. It is suggested that the goal of dyslipidaemic therapy should be to bring patient lipid-blood pressure plots below the threshold line so as to stabilize/reverse extant coronary atherosclerosis, apparent or inapparent, in the majority of dyslipidaemic patients.

Coronary Angiography↗
PubMed2026

COSIGT: population-scalable genotyping of complex loci from low-coverage sequencing data using pangenome graphs.

Pangenome graphs capture extensive structural diversity, but resolving complex loci from shallow sequencing remains challenging, particularly when samples are of low quality such as in ancient DNA. We introduce COSIGT (COsine SImilarity-based GenoTyper), which assigns diploid genotypes by matching read-depth distributions to haplotype paths via cosine similarity. Because this metric evaluates relative coverage profiles rather than absolute read counts, COSIGT substantially outperforms existing likelihood-based tools at low coverage (1-2X). We demonstrate scalability to thousands of modern and ancient genomes, enabling robust, population-scale analyses of complex variation directly from low-coverage datasets.

Humans↗
PubMed1993

Relationship between molecular connectivity and carcinogenic activity: a confirmation with a new software program based on graph theory.

For a database of 826 chemicals tested for carcinogenicity, we fragmented the structural formula of the chemicals into all possible contiguous-atom fragments with size between two and eight (nonhydrogen) atoms. The fragmentation was obtained using a new software program based on graph theory. We used 80% of the chemicals as a training set and 20% as a test set. The two sets were obtained by random sorting. From the training sets, an average (8 computer runs with independently sorted chemicals) of 315 different fragments were significantly (p < 0.125) associated with carcinogenicity or lack thereof. Even using this relatively low level of statistical significance, 23% of the molecules of the test sets lacked significant fragments. For 77% of the molecules of the test sets, we used the presence of significant fragments to predict carcinogenicity. The average level of accuracy of the predictions in the test sets was 67.5%. Chemicals containing only positive fragments were predicted with an accuracy of 78.7%. The level of accuracy was around 60% for chemicals characterized by contradictory fragments or only negative fragments. In a parallel manner, we performed eight paired runs in which carcinogenicity was attributed randomly to the molecules of the training sets. The fragments generated by these pseudo-training sets were devoid of any predictivity in the corresponding test sets. Using an independent software program, we confirmed (for the complex biological endpoint of carcinogenicity) the validity of a structure-activity relationship approach of the type proposed by Klopman and Rosenkranz with their CASE program.

Carcinogens↗
PubMed2025

PLNMFG: Pseudo-label guided non-negative matrix factorization model with graph constraint for single-cell multi-omics data clustering.

The development of single-cell multi-omics sequencing technologies has enabled the simultaneous analysis of multi-omics data within the same cell. Accurate clustering of these cells is crucial for downstream analyses of complex biological functions. Despite significant advances in multi-omics integration approaches, current methodologies exhibit two major limitations. First, they inadequately incorporate prior biological knowledge from various omic layers. Second, these methods often conduct independent dimensionality reduction on individual omic datasets, thereby failing to capture the intrinsic complementary information and potentially overlooking crucial cross-platform interactions. Motivated by these, this study investigates a non-negative matrix factorization model called PLNMFG, which integrates the unified latent representation learning that retains the features between and within omics and the cluster structure learning that retains the intrinsic structure of the data into one joint framework. Specially, PLNMFG performs adaptive imputation to handle dropout events and uses prior pseudo-labels as constraints during the process of collective non-negative matrix factorization, as a result, a more robust latent representation that preserves the double similarity information is obtained. Graph Laplacian constraint is applied during clustering which further preserves structure characteristic of multi-omics data. In addition, the weight of each omic is adaptively learned based on the omic contribution. A series of experiments on 8 benchmark datasets show that our model performs well in terms of clustering accuracy and computational efficiency.

Single-Cell Analysis↗
PubMed2024

Sparse spectral graph analysis and its application to gastric cancer drug resistance-specific molecular interplays identification.

Uncovering acquired drug resistance mechanisms has garnered considerable attention as drug resistance leads to treatment failure and death in patients with cancer. Although several bioinformatics studies developed various computational methodologies to uncover the drug resistance mechanisms in cancer chemotherapy, most studies were based on individual or differential gene expression analysis. However the single gene-based analysis is not enough, because perturbations in complex molecular networks are involved in anti-cancer drug resistance mechanisms. The main goal of this study is to reveal crucial molecular interplay that plays key roles in mechanism underlying acquired gastric cancer drug resistance. To uncover the mechanism and molecular characteristics of drug resistance, we propose a novel computational strategy that identified the differentially regulated gene networks. Our method measures dissimilarity of networks based on the eigenvalues of the Laplacian matrix. Especially, our strategy determined the networks' eigenstructure based on sparse eigen loadings, thus, the only crucial features to describe the graph structure are involved in the eigenanalysis without noise disturbance. We incorporated the network biology knowledge into eigenanalysis based on the network-constrained regularization. Therefore, we can achieve a biologically reliable interpretation of the differentially regulated gene network identification. Monte Carlo simulations show the outstanding performances of the proposed methodology for differentially regulated gene network identification. We applied our strategy to gastric cancer drug-resistant-specific molecular interplays and related markers. The identified drug resistance markers are verified through the literature. Our results suggest that the suppression and/or induction of COL4A1, PXDN and TGFBI and their molecular interplays enriched in the Extracellular-related pathways may provide crucial clues to enhance the chemosensitivity of gastric cancer. The developed strategy will be a useful tool to identify phenotype-specific molecular characteristics that can provide essential clues to uncover the complex cancer mechanism.

Stomach Neoplasms↗
PubMed1989

[Clinical studies on rotation and translation of mandibular head in internal derangements of the temporomandibular joint with dual axis graph].

The present study was aimed at establishing the standards for functional diagnosis of the internally deranged TMJ by analyzing the rotary and gliding movements of the mandibular head. The subjects were patients with anterior displacement of the articular disc (ADD) and normal persons. The rotary movements were examined by use of a simplified condylar movement recorder and a specially developed dual axis graphic system. The findings are as follows: 1. In the patients and the normal persons as well, the rotary movements near the intercuspal contact position (ICP) showed a tendency to increase anteriorly until the mandibular head moved up to 6 mm from the ICP. However, in both patients with ADD with reduction and without reduction, the rotary movements near the ICP were significantly large as compared with those in the normal subjects. 2. In the ordinary persons, the rotary movements near the ICP were mostly larger during the closing movements than during the opening movements. In both patients with ADD with reduction and without reduction, the rotary movements were larger during the opening movement than during the closing movement. 3. The results of our study suggest that the dual axis graph could be a useful tool in examining the rotary movement of the mandibular head.

Humans↗
PubMed2000

A simple method for obtaining original data from published graphs and plots.

OBJECTIVE: To describe a method for deriving original data values from scanned images of graphs and scatterplots published in the medical literature. CONCLUSION: The procedure is simple, reproducible, and relatively error free (when performed carefully). This method is useful in converting published graphic material into numeric data for various uses when the original data are unavailable directly from the authors.

Data Interpretation, Statistical↗
PubMed1996

Neural network simulation of visual inspection of graphs of single-subject interventions.

Judgments of the effectiveness of single-subject behavioral interventions are often based on visual examination of graphs of response data, but previous research indicates that such judgments are often unreliable and flawed. Here it is proposed that artificial neural networks could be developed to simulate the judgments of expert judges. A prototype of such a network was designed and trained in the present study, and its use in novel experiments matched the estimates of the expert whose judgments were simulated significantly better than did a prediction equation developed using a multiple regression approach.

Artificial Intelligence↗
PubMedDate not supplied

[Evaluation of genetic test redundancy using a high-frequency component of the l-gram graph].

Various approaches to the estimation of DNA redundancy are compared: the Shannon entropy, the Lempel-Ziv complexity, and a new method, the computation of the low-frequency component of the l-gram graph. Although these methods are based on different ideas, they satisfy some reasonable requirements. The ability of these methods to find various kinds of repeats in genetic texts is compared. The resolution of the new method for calculation of DNA redundancy is discussed on the example of well-known repeats in the Epstein-Barr virus genome. The intrinsic discrepancy of high-frequency profile and Shannon redundancy profile were observed in some functionally significant regions of sequences being investigated.

Base Sequence↗