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PubMed2003

Visualisation and graph-theoretic analysis of a large-scale protein structural interactome.

BACKGROUND: Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network. RESULTS: We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network. CONCLUSIONS: Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level.

Archaeal Proteins↗
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↗
PubMed2004

Graph rigidity and localization of multi-robot formations.

This paper provides theoretical foundation for the problem of localization in multi-robot formations. Sufficient and necessary conditions for completely localizing a formation of mobile robots/vehicles in SE(2) based on distributed sensor networks and graph rigidity are proposed. A method for estimating the quality of localizations via a linearized weighted least-squares algorithm is presented, which considers incomplete and noisy sensory information. The approach in this paper had been implemented in a multi-robot system of five car-like robots equipped with omni-directional cameras and IEEE 802.11b wireless network.

Journal Article↗
PubMed2004

Which is better for presenting your data: table or graph?

This study aimed at investigating the characteristics of table and graph that people perceive and the data types which people consider the two displays are most appropriate for. Participants in this survey were 195 teachers and under-graduates from four universities in Beijing. The results showed people's different attitudes towards the two forms of display.

China↗
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

Graphs: looking at relationships.

Research articles often incorporate data in the form of graphs. This article acts as a study guide to enable readers to understand and interpret the data produced in this way.

Audiovisual Aids↗
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↗
PubMedDate not supplied

[On connection of a graph of a gene network with qualitative modes of function].

Theoretical investigation of properties of assumed gene networks constructed from elementary units of two types, genetic elements and control links, was carried out. A test was formulated for a subclass of such networks with cyclic structure called S(n,k)-networks allowing calculation-free prediction of the network limiting properties (the presence/absence and number of stationery and/or cyclic functioning modes) from a graph of the network structure. The obtained data can be useful for constructing gene networks with predefined properties.

Genetics↗
PubMed1979

[An attempt to use graph theory for the description of demographic events].

"The possibility is discussed of using graphs to describe a sequence of demographic events such as births, marriages and deaths. Among all sequences of demographic events those with perturbations are singled out. The following perturbations are defined: childlessness, premature termination of childbearing caused by the death of the female or termination of marriage due to divorce or death of spouse, remarriage of females and pre-marital births." (SUMMARY IN ENG, RUS)

Demography↗
PubMedDate not supplied

[Graph of sodium channel states].

Four models of sodium channel are considered, only one of its state being conducting. Transitions between any two communicated states are suggested to be governed by the first order kinetics. It is shown that the model describes current responses to single step potentials as well as inactivation -- activation coupling, if its graph has a function between the conducting and inactivation states and the state filled at the hyperpolarization.

Electrophysiology↗
PubMed1999

[Application of power band graph method to the modeling and simulation of cardiovascular system].

This paper presents a computer simulation model of the cardiovascular circulation system, which describes the blood flow dynamic law in the cardiovascular system by the state equation. The model can be used in physiological study and computer-aided medical education. In this paper, the Power Band Graph (PBG) modeling method is used to realize modeling of the human circulation system and conduct a simulation study on a simplified physiological system model. The results demonstrate that the PBG method, as an understandable and unity modeling method, is quite effective and practicable and can be used widely in the field of physiological system simulation.

Computer Simulation↗
PubMedDate not supplied

Molecular descriptor based on a molar refractivity partition using Randic-type graph-theoretical invariant.

PURPOSE: Development of a novel semi-empirical descriptor (MR(chi) for molecular modelling. METHOD: The index is based on a molar refractivity partition using Randictype graph-theoretical invariant. RESULTS: This hybrid index describes not only the London dispersive forces in a ligand fragment related to the molar refractivity but also structural features of the molecule It is also applicable in Quantitative Structure-Activity Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) studies. CONCLUSIONS: The method is convenient and can discriminate between isomers.

Chemistry, Pharmaceutical↗
PubMed2003

[Clinical application of a software for the analysis of arterial blood gases graph in 231 patients with chronic obstructive pulmonary disease].

OBJECTIVE: To evaluate the clinical significance of a computer software for the analysis of arterial blood gases graph (ABGG) in chronic obstructive pulmonary disease(COPD). METHODS: The software was developed with Win98 as the operating platform and the visual software Delphi 5.0 from Borland Company, and it was used for evaluation of the changes in arterial blood gases (ABG) of 231 COPD cases. RESULTS: (1) With the software it took only (4.7+/-0.5)s to draw and analyze an ABGG of COPD patients during oxygen inhalation; the time was much shorter than manual analysis (90.2+/-4.9)s, P<0.001. (2) During acute attack, the distributions of the arterial blood gases parameters on ABGG were as follows: 55.4% of cases in the area of insufficient ventilation and deranged gas exchange (area 5), 22.9% of cases in the area of compensated ventilation and deranged gas exchange (area 4), 21.6% of cases in the area of excessive ventilation and deranged gas exchange (area 6). (3) When the COPD patient's condition improved, the location of ABG in ABGG shifted from area 5 to area 4 or area 6. The distributions of the arterial blood gases parameters on ABGG of 106 cases on admission were significantly different from those at the time of discharge. (4) With deterioration of patient's condition, it shifted to area 5. Before death, the arterial blood gases parameters were exclusively in the area 5. CONCLUSION: The computer software for ABGG shortened the time to draw and evaluate ABG during oxygen inhalation, and it could reflect the changes in patient's condition promptly.

Aged↗