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PubMed2026

FusionTarget: Computational framework for drug repurposing against modeled fusion protein structures from genomic breakpoints.

Many fusion genes have been recognized as biomarkers and therapeutic targets. However, the lack of knowledge on protein structures and targeting approaches made it challenging to develop effective targeting therapeutics. To fill this, we developed a computational pipeline, FusionTarget, which annotates the genomic DNA breakage to RNA and protein sequences, predicts the 3D structures of fusion proteins, and performs comparative virtual screening, comparative molecular dynamics simulation, and quantitative analyses to identify the fusion protein-selective small molecules by selecting drugs with consistent high-fold binding affinity between fusion and wild-type proteins in multiple isoforms. We applied our pipeline to EWSR1::FLI1 in Ewing sarcoma and KMT2A::AFF1 in infant acute lymphoblastic leukemia. Further cell assay experiments confirmed that cells expressing individual fusion genes were more sensitive to the suggested drugs, and the key downstream genes were affected by our drugs. FusionTarget provides a unique foundation for developing therapeutics targeting fusion proteins.

applied computing in medical science↗

PubMed2026

A python based automated computational framework to classify and comparative genomics analysis of the global diversity of chili leaf curl virus (ChiLCV) strains to understand virus host interactions.

Chili leaf curl virus (ChiLCV) is a Begomovirus chillicapsici that is one of the most devastating viruses impacted on the production of chili in the world, especially in South Asia. In the present study, we combined high-throughput computational genomics with experimental analysis of global diversity. A workflow was created using automated Python scripts to download, curate and process ChiLCV genomes from public database. About 410 complete ChiLCV genomes download from public databases. Using a phylogenetic approach, these isolates were subdivided into 34 strains, belonging to 10 major clades, showing significant genetic diversity. Geographic analysis revealed that Pakistan (207 isolates) and India (148 isolates) were the main sources of ChiLCV diversity and the remainder of the isolates were from Oman, Bangladesh, Iran, Saudi Arabia and Sri Lanka. Recombination was observed as a major evolutionary force as more than twenty recombination events were detected. Analysis of cis-regulatory elements showed a complex structure of the viral promoter, including multiple binding sites for transcription factors, hormone-response elements, light-responsive elements, and stress-responsive elements, indicating a high number of interactions between viral regulatory elements and host signaling pathways. Pangenome analysis showed the presence of a highly dynamic open pangenome made up of strain-specific orthologous groups (species-specific orthogroups). Experimental inoculation of chili plants was also carried out to assess the biological effects of infection, along with phytochemical, FTIR, HPLC, and qPCR analyses.

Begomovirus↗

PubMed1997

A general computational framework for modeling cellular structure and function.

The "Virtual Cell" provides a general system for testing cell biological mechanisms and creates a framework for encapsulating the burgeoning knowledge base comprising the distribution and dynamics of intracellular biochemical processes. It approaches the problem by associating biochemical and electrophysiological data describing individual reactions with experimental microscopic image data describing their subcellular localizations. Individual processes are collected within a physical and computational infrastructure that accommodates any molecular mechanism expressible as rate equations or membrane fluxes. An illustration of the method is provided by a dynamic simulation of IP3-mediated Ca2+ release from endoplasmic reticulum in a neuronal cell. The results can be directly compared to experimental observations and provide insight into the role of experimentally inaccessible components of the overall mechanism.

Animals↗

PubMed2005

A voting-based computational framework for visual motion analysis and interpretation.

Most approaches for motion analysis and interpretation rely on restrictive parametric models and involve iterative methods which depend heavily on initial conditions and are subject to instability. Further difficulties are encountered in image regions where motion is not smooth-typically around motion boundaries. This work addresses the problem of visual motion analysis and interpretation by formulating it as an inference of motion layers from a noisy and possibly sparse point set in a 4D space. The core of the method is based on a layered 4D representation of data and a voting scheme for affinity propagation. The inherent problem caused by the ambiguity of 2D to 3D interpretation is usually handled by adding additional constraints, such as rigidity. However, enforcing such a global constraint has been problematic in the combined presence of noise and multiple independent motions. By decoupling the processes of matching, outlier rejection, segmentation, and interpretation, we extract accurate motion layers based on the smoothness of image motion, then locally enforce rigidity for each layer in order to infer its 3D structure and motion. The proposed framework is noniterative and consistently handles both smooth moving regions and motion discontinuities without using any prior knowledge of the motion model.

Algorithms↗

PubMed2004

A computational framework for cortical learning.

Recent physiological findings have revealed that long-term adaptation of the synaptic strengths between cortical pyramidal neurons depends on the temporal order of presynaptic and postsynaptic spikes, which is called spike-timing-dependent plasticity (STDP) or temporally asymmetric Hebbian (TAH) learning. Here I prove by analytical means that a physiologically plausible variant of STDP adapts synaptic strengths such that the presynaptic spikes predict the postsynaptic spikes with minimal error. This prediction error model of STDP implies a mechanism for cortical memory: cortical tissue learns temporal spike patterns if these spike patterns are repeatedly elicited in a set of pyramidal neurons. The trained network finishes these patterns if their beginnings are presented, thereby recalling the memory. Implementations of the proposed algorithms may be useful for applications in voice recognition and computer vision.

Action Potentials↗

PubMed2002

TFBS: Computational framework for transcription factor binding site analysis.

MOTIVATION: TFBS is a set of integrated, object-oriented Perl modules for transcription factor binding site detection and analysis. It implements objects representing specificity profile matrices, binding sites and sets thereof, pattern generators, and pattern database interfaces. The modules are interoperable with the BioPerl open source system. AVAILABILITY AND SUPPLEMENTARY INFORMATION: The module package with documentation and example scripts are available at http://forkhead.cgb.ki.se/TFBS/

Binding Sites↗

PubMed2004

Giving form to the function of the heart: embedding cellular models in an anatomical framework.

A computational framework is presented for integrating the electrical, mechanical, and biochemical functions of the heart. The construction of efficient finite element representations of canine and porcine ventricular geometry and microstructure is outlined. Computational techniques are applied to solve large deformation soft tissue mechanics by using orthotropic constitutive laws for myocardial tissue and models of active tension generation embedded at the Gauss points in the finite element mesh. The reaction-diffusion equations governing electrical current flow in the heart are solved on a grid of deforming material points that access systems of ordinary differential equations representing the cellular processes underlying the cardiac action potential. Navier-Stokes equations are solved to predict coronary blood flow in a system of branching blood vessels embedded in the deforming myocardium.

Animals↗

PubMedDate not supplied

Description and initial applications of the Staggers & Parks Nurse-Computer Interaction Framework.

The authors developed a nurse-computer interaction framework by integrating concepts from human-computer interaction, nursing informatics, and developmental psychology. In this framework, nurses and computers interact in a system of mutual influences, with information being the medium of exchange between them. Nurse behaviors and computer interface actions occur according to their respective characteristics. In turn, the nurse-computer dyad is embedded within a nursing context and moves along a nursing informatics developmental trajectory. A sample of findings from empirical studies is placed in the framework, and framework uses are described.

Computer Simulation↗

PubMed2025

A computational ontology framework for the synthesis of multi-level pathology reports from brain MRI scans.

BackgroundConvolutional neural network (CNN) based volumetry of MRI data can help differentiate Alzheimer's disease (AD) and the behavioral variant of frontotemporal dementia (bvFTD) as causes of cognitive decline and dementia. However, existing CNN-based MRI volumetry tools lack a structured hierarchical representation of brain anatomy, which would allow for aggregating regional pathological information and automated computational inference.ObjectiveDevelop a computational ontology pipeline for quantifying hierarchical pathological abnormalities and visualize summary charts for brain atrophy findings, aiding differential diagnosis.MethodsUsing FastSurfer, we segmented brain regions and measured volume and cortical thickness from MRI scans pooled across multiple cohorts (N = 3433; ADNI, AIBL, DELCODE, DESCRIBE, EDSD, and NIFD), including healthy controls, prodromal and clinical AD cases, and bvFTD cases. Employing the Web Ontology Language (OWL), we built a semantic model encoding hierarchical anatomical information. Additionally, we created summary visualizations based on sunburst plots for visual inspection of the information stored in the ontology.ResultsOur computational framework dynamically estimated and aggregated regional pathological deviations across different levels of neuroanatomy abstraction. The disease similarity index derived from the volumetric and cortical thickness deviations achieved an AUC of 0.88 for separating AD and bvFTD, which was also reflected by distinct atrophy profile visualizations.ConclusionsThe proposed automated pipeline facilitates visual comparison of atrophy profiles across various disease types and stages. It provides a generalizable computational framework for summarizing pathologic findings, potentially enhancing the physicians' ability to evaluate brain pathologies robustly and interpretably.

Humans↗

PubMed1998

Designing computer-based frameworks that facilitate doctor--patient collaboration.

A current trend in medicine involves establishing collaborative problem solving between patients and physicians in order to involve patients more in their own care. Neither diagnosis nor therapy can be completely successful unless the patient and the doctor understand each other and collaborate with each other in an effort to gauge the other's requests, needs and concerns. This is made even more difficult by the fact that there is often a big difference between the doctors and patients in terms of expectations, vocabulary used, and other factors. For diagnosis of many disorders, a detailed description of the problem and of the patient's history are required. For therapy, patients must understand how and when to take prescribed drugs, what changes to make in diet, exercise, or lifestyle and why they are important. This paper describes a model of asynchronous collaboration between people with very different knowledge of medicine in which a computer framework attempts to mediate between patients and physicians and reduce some of the differences in communication. It allows patients to pace themselves in familiarizing themselves with the relevant domain terms, some of the medical factors underlying the conditions under question, and the justifications and implications of the prescribed treatment plan. It also allows physicians to request more information of patients and gives patients contextual information to help them understand the underlying reasons for the questions. This framework has been partially implemented in the domain of migraines. As described in the paper, not only is the system designed to cooperate with the patient, but using the system also results in better mutual understanding between the doctor and the patient, thus leading to better collaboration between them.

Artificial Intelligence↗

PubMed2001

A modeling study of water quality in main channel and estuarine wetland.

A simple computation framework is applied to include estuarine wetland and their interaction with main channels in estuarine modeling. The concept and the model implementation of the scheme are explained using a vertical two-dimensional model of estuarine hydrodynamics and water quality. The model was applied to the Tanshui River estuary and Kuan-Du wetland. The model is calibrated and verified by the available measured data. Simulations are also conducted for various upstream freshwater discharges to predict water quality in the main channel and estuarine wetland. The results show that the inclusion of estuarine wetland in a water-quality model not only provides a framework for computing water-quality conditions but also accounts for the interaction between wetland and main channel. The model provides a useful tool for environmental planning, protection and proposed wetland restoration works.

Conservation of Natural Resources↗

PubMed2005

Fast and simple calculus on tensors in the log-Euclidean framework.

Computations on tensors have become common with the use of DT-MRI. But the classical Euclidean framework has many defects, and affine-invariant Riemannian metrics have been proposed to correct them. These metrics have excellent theoretical properties but lead to complex and slow algorithms. To remedy this limitation, we propose new metrics called Log-Euclidean. They also have excellent theoretical properties and yield similar results in practice, but with much simpler and faster computations. Indeed, Log-Euclidean computations are Euclidean computations in the domain of matrix logarithms. Theoretical aspects are presented and experimental results for multilinear interpolation and regularization of tensor fields are shown on synthetic and real DTI data.

Algorithms↗

PubMed2006

An automatic variational level set segmentation framework for computer aided dental X-rays analysis in clinical environments.

An automatic variational level set segmentation framework for Computer Aided Dental X-rays Analysis (CADXA) in clinical environments is proposed. Designed for clinical environments, the segmentation contains two stages: a training stage and a segmentation stage. During the training stage, first, manually chosen representative images are segmented using hierarchical level set region detection. Then the window based feature extraction followed by principal component analysis (PCA) is applied and results are used to train a support vector machine (SVM) classifier. During the segmentation stage, dental X-rays are classified first by the trained SVM. The classifier provides initial contours which are close to correct boundaries for three coupled level sets driven by a proposed pathologically variational modeling which greatly accelerates the level set segmentation. Based on the segmentation results and uncertainty maps that are built based on a proposed uncertainty measurement, a computer aided analysis scheme is applied. The experimental results show that the proposed method is able to provide an automatic pathological segmentation which naturally segments those problem areas. Based on the segmentation results, the analysis scheme is able to provide indications of possible problem areas of bone loss and decay to the dentists. As well, the experimental results show that the proposed segmentation framework is able to speed up the level set segmentation in clinical environments.

Algorithms↗

PubMedDate not supplied

The IUPS Physiome Project: a framework for computational physiology.

The IUPS Physiome Project is an internationally collaborative open-source project to provide a public domain framework for computational physiology, including the development of modelling standards, computational tools and web-accessible databases of models of structure and function at all spatial scales. A number of papers in this volume deal with the development of specific mathematical models of physiological processes. This paper stands back from the detail of individual models and reviews the current state of the IUPS Physiome Project including organ and organ system continuum models, the interpretation of constitutive law parameters in terms of micro-structural models, and markup languages for standardizing cellular processes. Some current practical applications of the physiome models are given and some of the challenges for the next 5 years of the Physiome Project at the level of organs, cells and proteins are proposed.

Cell Physiological Phenomena↗

PubMed2005

Differential fly-throughs (DFT): a general framework for computing flight paths.

In this paper, we propose a new variational framework based on distance transform and gradient vector flow, to compute flight paths through tubular and non-tubular structures, for virtual endoscopy. The proposed framework propagates two wave fronts of different speeds from a point source voxel, which belongs to the medial curves of the anatomical structure. The first wave traverses the 3D structure with a moderate speed that is a function of the distance field to extract its topology, while the second wave propagates with a higher speed that is a function of the magnitude of the gradient vector flow to extract the flight paths. The motion of the fronts are governed by a nonlinear partial equation, whose solution is computed efficiently using the higher accuracy fast marching level set method (HAFMM). The framework is robust, fully automatic, and computes flight paths that are centered, connected, thin, and less sensitive to boundary noise. We have validated the robustness of the proposed method both quantitatively and qualitatively against synthetic and clinical datasets.

Algorithms↗

PubMed2026

A reproducible computational transcriptomic framework for cell-type-resolved fibroinflammatory-AKT remodeling in human heart failure.

BACKGROUND: Human heart failure involves multicellular transcriptional remodeling, but public transcriptomic studies often remain disconnected from cell-type localization and perturbational interpretation. METHODS: We developed a reproducible computational workflow integrating human left-ventricular bulk transcriptomes, donor-level cell-type pseudobulk results from a human heart-failure single-cell/single-nucleus atlas, external snRNA-seq support, curated module scoring, focused ligand-receptor prioritization and LINCS/L1000 perturbational matching. RESULTS: Cross-cohort analysis identified 14,358 same-direction HF-associated genes, including 1633 replicated HF-up and 785 replicated HF-down genes. Donor-level pseudobulk analysis localized disease remodeling to cardiomyocyte, fibroblast and myeloid compartments. Activated fibroblast and inflammatory myeloid programs defined a fibroinflammatory remodeling axis connected to context-dependent AKT-associated transcriptional shifts. External snRNA-seq support was strongest for fibroblast activation and AKT-associated remodeling, with etiology-dependent heterogeneity across validation resources. L1000FWD screening prioritized safety-aware perturbational hypotheses, including glimepiride and simvastatin as interpretable candidates requiring experimental validation. CONCLUSIONS: This study provides a computational transcriptomic framework linking reproducible human HF signatures, cell-type-resolved fibroinflammatory remodeling and perturbational genomic prioritization without claiming drug efficacy or AKT causality.

Humans↗

PubMed2001

An open and flexible framework for computer aided surgical training.

During the past year we have developed a new surgical skills training application called LapSim. We intend to describe the design, architecture and concepts of the software framework we have developed concurrently with the application. The framework is based on the concept of a classroom with students and teachers. Students, courses and results are stored in a centralized database and can be retrieved for review or modification. The students can also monitor their progress relative to other students or experts.

Computer Systems↗

PubMed2006

76-space analysis of grey matter diffusivity: methods and applications.

Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) allow in vivo investigation of molecular motion of tissue water at a microscopic level in cerebral gray matter (GM) and white matter (WM). DWI/DTI measure of water diffusion has been proven to be invaluable for the study of many neurodegenerative diseases (e.g., Alzheimer's disease and Creutzfeldt-Jakob disease) that predominantly involve GM. Thus, quantitative analysis of GM diffusivity is of scientific interest and is promised to have a clinical impact on the investigation of normal brain aging and neuropathology. In this paper, we propose an automated framework for analysis of GM diffusivity in 76 standard anatomic subdivisions of gray matter to facilitate studies of neurodegenerative and other gray matter neurological diseases. The computational framework includes three enabling technologies: (1) automatic parcellation of structural MRI GM into 76 precisely defined neuroanatomic subregions ("76-space"), (2) automated segmentation of GM, WM and CSF based on DTI data, and (3) automatic measurement of the average apparent diffusion coefficient (ADC) in each segmented GM subregion. We evaluate and validate this computational framework for 76-space GM diffusivity analysis using data from normal volunteers and from patients with Creutzfeldt-Jakob disease.

Adult↗