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PubMed1978

Bond graph models for plant biosystems.

Computable dynamic models for plant biosystems permit the study of effects of environmental variables on plant growth and productivity. Using bond graphs, a comprehensive phenomenological model of a plant biosystem may be developed and used in computer simulations. Elements of a model studied in this papaer include a gas diffusion network between the atmosphere and leaf cytoplasm, intracellular chemistry, and the translocation networks of the phloem. Bond graphs are shown to provide a conceptual basis for the development of biological subsystem and system models and lead to computable representations.

Atmosphere↗

PubMed1991

Structural analysis of neural circuits using the theory of directed graphs.

A new approach to analysis of structural properties of biological neural circuits is proposed based on their representation in the form of abstract structures called directed graphs. To exemplify this methodology, structural properties of a biological neural network and randomly wired circuits (RC) were compared. The analyzed biological circuit (BC) represented a sample of 39 neural nuclei which are responsible for the control of the cardiovascular function in higher vertebrates. Initially, direct connections of both circuits were stored in a square matrix format. Then, standard algorithms derived from the theory of directed graphs were applied to analyze the pathways of the circuits according to their length (in number of synapses), degree of connectedness, and structural strength. Thus, the BC was characterized by the presence of short, reciprocal, and unidirectional pathways which presented a high degree of heterogeneity in their strengths. This heterogeneity was mainly due to the existence of a small cluster of reciprocally connected neural nuclei in the circuit that have access, through short pathways, to most of the network. On the other hand, RCs were characterized by the presence of long and mainly reciprocal pathways which showed lower and absolute homogeneous strengths. Through this study the proposed methodology was demonstrated to be a simple and efficient way to store, analyze, and compare basic neuroanatomical information.

Animals↗

PubMed1989

The automation of routine calculations and graphing for alkaline filter elution analysis on a computer-controlled liquid scintillation analyzer.

The data calculations and graphing functions for the widely used alkaline filter elution technique have been completely automated. This saves considerable time and increases both efficiency and accuracy by eliminating human error. The automation was accomplished utilizing Lotus 1-2-3 and Lotus Graphwriter II on a Packard Tri-Carb 1900CA liquid scintillation analyzer containing a built-in pico-XTE computer. A batch file is used to control the overall execution of the process. It copies the data stored by the 1900CA into the Lotus subdirectory and invokes Lotus 1-2-3. A Lotus macro automatically imports the data file, performs the calculations, and prints the results. Graphwriter II is then invoked by the batch file and the charts are composed and graphed. Finally, the instrument operating software for the 1900CA is reentered and sample analysis can be resumed for any unanalyzed samples.

Alkalies↗

PubMed1992

Automated site-directed drug design: a method for the generation of general three-dimensional molecular graphs.

A new algorithm for creating diverse, irregular and physically reasonable three-dimensional linear atomic chains is described. The linear chains of atoms, or molecular graphs, are generated by solving a series of trigonometric equations within geometric constraints for a given set of atom types. The nature and number of the chains that are produced can be controlled by changing the palette of atom types, so that a chemist user could generate template suggestions that are synthetically relevant to a drug design project. Testing has shown that the method is sufficiently robust to be used in a general context. The molecular graphs could serve as useful structural templates for joining up regions in an active site where a ligand might interact strongly with the receptor. This paper is concerned with the description and proof of the methodology. The approach will form part of a larger structural tool kit for helping chemists to design novel ligands for a specified site.

Algorithms↗

PubMed1991

Identification of regulatory properties of metabolic networks by graph theoretical modeling.

An earlier graph theoretical model of metabolic and gene-expression networks has been modified and extended to include the effect of electrical potentials on binding constants, representation of uncatalyzed processes, and treatment of parallel reactions catalyzed by a single enzyme. Formal operations on the graph, which are facilitated by a set of standardized guidelines, identify the feedback signals in the network and rank them according to their influence. The technique was applied to a model of glycolysis in ascites tumor cells in the absence and presence of 12.5 mM exogenous glucose. Feedback regulation was widely distributed and mostly due to binding of adenine nucleotide cofactors to the enzymes of the network. The major changes in feedback regulation on adding glucose is the relief of inhibition of hexokinase and phosphofructokinase and the activation of pyruvate kinase. We conclude that regulation of tumor cell glycolysis is not restricted to hexokinase or to (Na+,K+)-ATPase as was previously suggested by others.

Animals↗

PubMed1989

How-often-that-high graphs of serum cholesterol. Findings from the Scottish Heart Health and Scottish MONICA studies.

The Scottish Heart Health and Scottish MONICA studies included measurements of serum total cholesterol in 10,450 representative men and women aged 25-64 years recruited across Scotland in 1984-86. The results were typical of Britain as a whole. A new graph, called the HOTH graph ("how often that high?"), shows the percentage of the population with serum total cholesterol at or above any given value. Median (equal to mean) cholesterol levels in men were 5.5, 6.0, 6.3, and 6.2 mmol/l in successive 10-year age groups 25-64, whilst equivalent values in women were 5.2, 5.5, 6.4, and 7.2 mmol/l. By comparison with other countries these are high, but the percentage of the population above specific cutpoints is disproportionate, varying considerably by age and sex. Application of imported cholesterol management algorithms, based on global cut-points, would lead to an overwhelming caseload of patients needing intensive lipid investigation and management, dominated by older women, and incurring great costs. 35% of the population 25-64 years old would be at or above 6.5 mmol/l and 11% at or above 7.8 mmol/l. A population diet and multiple-risk-factor strategy would be more feasible and rational than a one-dimensional cholesterol cut-point approach.

Adult↗

PubMed1990

Computational techniques for vertex partitioning of graphs.

A powerful vertex-partitioning algorithm is developed and applied for vertex partitioning of graphs of chemical and spectroscopic interest. The codes developed on the basis of these algorithms are tested and compared for performance with other methods based on the Morgan algorithm and the principal eigenvector algorithm based on the Givens-Householder method. The newly developed algorithm and codes appear to be more powerful than the Morgan and the principal eigenvector algorithms for vertex partitioning of graphs.

Chemistry, Physical↗

PubMed1992

Timing of physiodesis in limb length inequality. The Straight Line Graph applied in 30 patients.

In a prospective study 30 children underwent 33 physiodeses for lower limb length inequality (LLI). Timing of surgery was based on (bi)annual orthoradiographic measurements and skeletal age, and in accordance with Moseley's Straight Line Graph. The mean predicted LLI was 5.2 (3.0-11) cm and the mean LLI at the end of growth was 1.4 (0.0-4.3) cm. In 9 patients final LLI exceeded 1.5 cm, and one of these patients was operated on twice. In total, secondary operations were performed three times. After analysis of the failures it is concluded that the accuracy of the Straight Line Graph is mainly limited by the pattern of skeletal maturation. Recommendations to prevent failures from other causes are given.

Adolescent↗

PubMed2025

monarchr: an R package for querying biomedical knowledge graphs.

SUMMARY: Biomedical knowledge graphs (KGs) aggregate and provide a wealth of information, linking genes and their variants, diseases, phenotypes, and much more. While these data are available in raw and API-hosted form, to date, functionality for working with KGs in the R programming language has been limited. We introduce monarchr, a package for querying and manipulating KG data. Support for the expansive Monarch Initiative KG is built in, and monarchr can accommodate any KG in the Knowledge Graph eXchange (KGX) format. This tidy-inspired interface offers researchers an intuitive, iterative approach to querying and visualizing KG data. AVAILABILITY AND IMPLEMENTATION: Source code, documentation, and installation instructions are available at https://github.com/monarch-initiative/monarchr.

Software↗

PubMed2026

EPIC: Event Prototyping via Information Constrained graph learning for personalized cancer driver gene prediction.

MOTIVATION: Precision oncology relies on accurately distinguishing patient-specific driver mutations from the vast background of passenger alterations. While graph-based computational methods have emerged as powerful tools for this task, they often struggle to preserve the distinct genomic context of individual mutations within complex biological networks. Consequently, subtle patient-specific driver signals are frequently obscured by dominant topological patterns, critically impeding the identification of individualized oncogenic events essential for personalized cancer therapy. RESULTS: To address this, we propose EPIC, a novel framework for Event Prototyping via Information Constrained Graph Learning. Unlike traditional node-centric approaches, EPIC redefines driver prediction as a metric learning task in an event embedding space. We introduce an information-constrained learning strategy that imposes explicit geometric constraints on feature variance, effectively preventing feature collapse and ensuring that low-frequency driver signals are distinctively preserved. Experiments on large-scale cancer cohorts demonstrate that EPIC significantly outperforms established baselines. Notably, the model prioritizes low-frequency driver variants typically overlooked by population-based methods, mapping them to critical oncogenic mechanisms associated with drug resistance and metastasis. Furthermore, clinical actionability analysis confirms that EPIC substantially expands the patient population eligible for targeted therapies. EPIC provides a robust and context-aware solution for personalized cancer driver discovery, bridging the gap between genomic data and actionable therapeutic insights. AVAILABILITY AND IMPLEMENTATION: The source code and datasets are available at https://github.com/spcho-dev/EPIC.

Humans↗

PubMed2026

VirBinn improves viral genome binning from metagenomic Hi-C through graph diffusion.

MOTIVATION: Metagenomic Hi-C provides in situ proximity signals that can improve genome binning and enable virus-host-association analysis. However, viral genome recovery remains difficult because virus-virus Hi-C contact matrices are extremely sparse. Viral genomes are small, often low-abundance, and frequently assemble into short contigs, leaving many true within-genome links unobserved and causing viral bins to fragment. RESULTS: We present VirBinn, a graph-diffusion framework for viral binning from metagenomic Hi-C. VirBinn enhances virus-virus connectivity through two complementary mechanisms: random-walk-with-restart enhancement on the sparse virus-virus contact graph and host-guided diffusion that propagates viral seeds through the host network to infer indirect virus-virus associations. The enhanced views are integrated and clustered using Leiden community detection to produce viral metagenome-assembled genomes (vMAGs). On dataset-specific simulation benchmarks with ground truth, VirBinn consistently recovers more high-quality vMAGs than Hi-C-based and shotgun-based baselines and substantially increases the number of near-complete genomes. On four real metagenomic Hi-C datasets spanning human gut, pig gut, sheep gut (long-read assembly), and wastewater, VirBinn yields more high-completeness vMAGs under CheckV and produces bins with strong within-cluster contact support. Finally, host linkage analysis using reconstructed host MAGs reveals habitat-specific host-association patterns and plausible host taxonomic profiles. AVAILABILITY AND IMPLEMENTATION: VirBinn is available at https://github.com/dyxstat/VirBinn. The scripts to reproduce the results and figures in this article are available at https://github.com/dyxstat/Reproduce_VirBinn.

Genome, Viral↗

PubMed2026

GT-Mamba: a Topology-Aware Graph-State space model for robust and interpretable epigenetic age prediction.

MOTIVATION: Current epigenetic clocks face a trade-off between predictive accuracy and biological interpretability, often relying on dataset-specific correction to generalize across cohorts. We propose GT-Mamba, a novel architecture that integrates a Structure-Aware Graph Transformer with the Mamba state space model. This design captures CpG topological correlations and genome-wide long-range dependencies. RESULTS: GT-Mamba demonstrates strong out-of-the-box robustness across heterogeneous independent validation cohorts, achieving a weighted average MAE of 4.43 years. Notably, it effectively generalizes to EPIC 850k arrays despite partial feature missingness, and maintains consistent performance across homologous age distribution shifts (MAE 2.94 years in a young cohort). Ablation studies confirm that graph topology contributes to improved robustness against noise. Mechanistic analysis suggests that the model captures methylation patterns associated with both developmental and functional processes. AVAILABILITY: Source code and pre-trained models are freely available at https://github.com/NENUBioCompute/GT-Mamba and archived on Zenodo (DOI: 10.5281/zenodo.19703155).

Epigenesis, Genetic↗

PubMed1990

A computer designed graph for administration of atracurium by i.v. infusion.

A bi-exponential mathematical computer model was used to develop a guidance graph for atracurium infusions. The model permitted variation in infusion rates, in pharmacokinetic parameters and in "effect" thresholds. Systematic experiments revealed a relationship between the rate of recovery from a fixed bolus loading dose and the most appropriate initial infusion rate. This relationship was expressed as a guidance graph or "ready reckoner". The quality of guidance was assessed in 50 anaesthetics, given consecutively. In 39 patients optimal myoneural block for surgery was maintained for the duration of the infusion without adjustments or supplementary bolus doses. The mean operating time was 92 min and the mean duration of infusion was 59 min.

Adult↗

PubMed2025

Reference-Free Variant Calling with Local Graph Construction with ska lo (SKA).

The study of genomic variants is increasingly important for public health surveillance of pathogens. Traditional variant-calling methods from whole-genome sequencing data rely on reference-based alignment, which can introduce biases and require significant computational resources. Alignment- and reference-free approaches offer an alternative by leveraging k-mer-based methods, but existing implementations often suffer from sensitivity limitations, particularly in high mutation density genomic regions. Here, we present ska lo, a graph-based algorithm that aims to identify within-strain variants in pathogen whole-genome sequencing data by traversing a colored De Bruijn graph and building variant groups (i.e. sets of variant combinations). Through in silico benchmarking and real-world dataset analyses, we demonstrate that ska lo achieves high sensitivity in single-nucleotide polymorphism (SNP) calls while also enabling the detection of insertions and deletions, as well as SNP positioning on a reference genome for recombination analyses. These findings highlight ska lo as a simple, fast, and effective tool for pathogen genomic epidemiology, extending the range of reference-free variant-calling approaches. ska lo is freely available as part of the SKA program (https://github.com/bacpop/ska.rust).

Polymorphism, Single Nucleotide↗

PubMed1991

Similarity graphing and enzyme-reaction database: methods to detect sequence regions of importance for recognition of chemical structures.

We developed a new method which searches sequence segments responsible for the recognition of a given chemical structure. These segments are detected as those locally conserved among a sequence to be analyzed (target sequence) and a set of sequences (reference sequences). Reference sequences are the sequences of functionally related proteins, ligands of which contain a common chemical substructure in their molecular structures. 'Similarity graphing' cuts target sequences into segments, aligns them with reference sequence pairwise, calculates the degree of similarity for each alignment, and shows graphically cumulative similarity values on target sequence. Any locally conserved regions, short or long in length and weak or strong in similarity, are detected at their optimal conditions by adjusting three parameters. The 'enzyme-reaction database' contains chemical structures and their related enzymes. When a chemical substructure is input into the database, sequences of the enzymes related to the input substructure are systematically searched from the NBRF sequence database and output as reference sequences. Examples of analysis using similarity graphing in combination with the enzyme-reaction database showed a great potentiality in the systematic analysis of the relationships between sequences and molecular recognitions for protein engineering.

Algorithms↗

PubMed2026

SwinePan for pig graph-based pangenome and multiomics data mining.

Pigs are one of the most important livestock species worldwide. Although multiple high-quality reference genomes exist, reliance on a single linear reference limits the detection of structural variants (SVs) and the characterization of population-specific genetic diversity. To address this limitation, we developed SwinePan, a comprehensive and integrated multiomics database for pigs built on a graph-based pangenome framework. SwinePan incorporates a variome derived from the graph-based pangenome, covering 2,598 individuals across 35 breeds, including 185,759 SVs, 117 million SNPs, and 6.8 million indels. The database also integrates transcriptomic data from liver, loin muscle, abdominal fat, and backfat, along with over 150,000 phenotypic records. The online toolkit deployed in SwinePan enables genome-wide association studies (GWAS), expression quantitative trait locus (eQTL) mapping, and colocalization, while interactive modules visualize population structure and multiomics associations, streamlining candidate gene and variant exploration. Additionally, two proof-of-concept analyses demonstrate how SwinePan pinpoints trait-associated loci and deciphers their potential regulatory mechanisms.

Journal Article↗

PubMed1992

An approach based on two-dimensional graph theory for structural cluster detection and its histopathological application.

An approach based on graph theory is described for detecting clusters of cells in tissue specimens (two-dimensional space). With a set of discrete basic elements (cell nuclei) having several measurable features (area, surface, main and minor axis of best-fitting ellipses) a graph is defined as having attributes associated with edges. Different minimum spanning trees (MSTs) can be constructed using different weight functions on the attributes (attributed MST). Analysis of the MST and of an attributed MST by use of a decomposition function allows detection of image areas with similar local properties. These clusters, which are then clusters of the tree, describe, for example, partial growth in different directions in a case of a human fibrosarcoma assuming that tumour cell nuclei are homogeneous with respect to their configuration and size. The model allows the separation of clusters of tumour cells growing in different directions and the approximation of the different growth angles. This decomposition also allows us to create new (higher) orders of structure (cluster tree).

Algorithms↗

PubMed1990

Community people's preference of hand drawn face graph as a health informing device.

Although the cartoon of a face is an effective device to visualize the image of numerical indices, its use is not popular among community health personnel. In the present study, we used the face graph as an aid for health informing and educating activities in the setting of a community health activity. For this purpose, we designed a special sheet to draw face by hand. By using this sheet, each person can draw his/her 'face' from one's laboratory data index under the guidance of additional lines. The acceptability of this hand drawn face was evaluated by 283 people aged 65 years and over at a health counseling session. For both men and women, a higher percentage preferred face (37% for men, 40% for women) over numeral (23% for men, 17% for women). The preference for the face graph was also observed at each of three age groups within each sex. The highest affinity to face (64%) was observed for the 14 women who reported as cataract patients.

Aged↗