Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “computational frameworks”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17Linked to original sources
PubMed2001

The role of activity-dependent network depression in the expression and self-regulation of spontaneous activity in the developing spinal cord.

Spontaneous episodic activity occurs throughout the developing nervous system because immature circuits are hyperexcitable. It is not fully understood how the temporal pattern of this activity is regulated. Here, we study the role of activity-dependent depression of network excitability in the generation and regulation of spontaneous activity in the embryonic chick spinal cord. We demonstrate that the duration of an episode of activity depends on the network excitability at the beginning of the episode. We found a positive correlation between episode duration and the preceding inter-episode interval, but not with the following interval, suggesting that episode onset is stochastic whereas episode termination occurs deterministically, when network excitability falls to a fixed level. This is true over a wide range of developmental stages and under blockade of glutamatergic or GABAergic/glycinergic synapses. We also demonstrate that during glutamatergic blockade the remaining part of the network becomes more excitable, compensating for the loss of glutamatergic synapses and allowing spontaneous activity to recover. This compensatory increase in the excitability of the remaining network reflects the progressive increase in synaptic efficacy that occurs in the absence of activity. Therefore, the mechanism responsible for the episodic nature of the activity automatically renders this activity robust to network disruptions. The results are presented using the framework of our computational model of spontaneous activity in the developing cord. Specifically, we show how they follow logically from a bistable network with a slow activity-dependent depression switching periodically between the active and inactive states.

Animals↗
PubMed1988

Cohort parity analysis: statistical estimates of the extent of fertility control.

Cohort parity analysis (CPA) is a method for indirect measurement of the extent and timing of the adoption of fertility control within marriage. It uses information on the parity distribution of a cohort of women of specified marriage ages and durations. A multinomial model of parity provides a convenient framework for the computation of distributional parameters describing the extent to which marital fertility control has been accepted and characterizing the way control has been used within specific durations of marriage. This leads to a pair of easily implemented formulas for upper- and lower-bound estimates of the expected proportion of the population ever controlling and the distribution of controllers by parity. The power of CPA is illustrated, using census data for currently married couples in Dublin, Belfast, and other county boroughs of Ireland in 1911.

Adult↗
PubMed1984

CT of the nasopharyngeal region. Normal and pathologic anatomy.

The soft tissue anatomy of the nasopharynx is presented in terms of deglutitional and masticatory muscle layers. Within this framework of analysis, computed tomography can detect relatively early soft tissue changes of nasopharyngeal carcinoma.

Deglutition↗
PubMed1994

Digital archives and communication highways in health care require a second look at the legal framework of the seventies.

The present state of the art and the state of practice regarding legal aspects of medical informatics are reported. Examples are taken from networking, archiving, and virtual reality. It is derived that the data protection concepts of the seventies are covering only some legal aspects of the application scene today and in the future. Thus a far wider legal approach is necessary. It can only be mastered if engineers and lawyers discuss future trends and derive together a new legal framework for medical computer systems in the late nineties. As computers will be everywhere from childhood to death the key issue is not to just protect an individual but to positively frame an information society.

Computer Communication Networks↗
PubMed1993

The receptor revolution--multiplicity of G-protein-coupled receptors.

The superfamily of G-protein-coupled receptors (GPCR) is probably the largest protein-encoding gene family in our genome. It is already known to include hundreds of members and many more are expected to emerge as the molecular cloning revolution proceeds. By definition the GPCR respond to ligands by interacting with intracellular G-proteins and thereby transduce external signals to the interior of the cell. A large body of evidence suggests that the GPCR are organized in the cell membrane like bacteriorhodopsin (BR). All GPCR possess seven hydrophobic membrane-spanning segments which seem to form a characteristic BR-like barrel structure. Thus, the three-dimensional structure of BR may be used as a framework for computer-aided structural modelling of GPCR. The ligands which activate the various members of the GPCR family include an enormous variety of molecules such as amines, amino acids and peptides as well as several small hydrophobic molecules. Many ligands bind to multiple distinct GPCR, e.g. neuropeptide Y (NPY). We have isolated molecular clones encoding a human NPY receptor whose binding properties conform to those of the Y1 subtype. This clone will be a useful tool in our efforts to unravel the molecular mechanisms of the many physiological functions of neuropeptide Y.

Amino Acid Sequence↗
PubMed2005

Adaptive algorithms for first principal eigenvector computation.

The paper presents a unified framework to derive and analyze 10 different adaptive algorithms, some well-known, to compute the first principal eigenvector of the correlation matrix of a random vector sequence. Since adaptive principal eigenvector algorithms have originated from a diverse set of disciplines, including ad hoc methods, it is necessary to examine them in a unified framework. In a common framework consisting of five steps, we analyze the derivation, convergence, and rate results for many well-known algorithms as well as two new adaptive algorithms. In the process, we offer fresh perspectives on the known algorithms, and derive new results for others. The common framework also allows us to comparatively study the 10 algorithms. Finally, we show experimental results to support our analyses.

Algorithms↗
PubMed2025

Automating candidate gene prioritization with large language models: from naive scoring to literature-grounded validation.

MOTIVATION: Identifying promising therapeutic targets from thousands of genes in transcriptomic studies remains a major bottleneck in biomedical research. While large language models (LLMs) show potential for gene prioritization, they suffer from hallucination and lack systematic validation against expert knowledge. RESULTS: The framework identified 609 sepsis-relevant genes with >94% filtering efficiency, demonstrating strong enrichment for inflammatory pathways including TNF-α signaling, complement activation, and interferon responses. Literature validation yielded 30 ultra-high confidence therapeutic candidates, including both established sepsis genes (IL10, TREM1, S100A9, NLRP3) and novel targets warranting investigation. Benchmark validation against expert-curated databases achieved 71.2% recall, with systematic correlation between computational confidence and evidence quality. The final candidate set balanced discovery (11 novel genes) with validation (19 known genes), maintaining biological coherence throughout the filtering process. This framework demonstrates that rigorous methodology can transform unreliable LLM outputs into systematically validated biological insights. By combining computational efficiency with literature grounding, the approach provides a practical tool for prioritizing experimental validation efforts. The modular design enables adaptation to other diseases through knowledge base substitution, offering a systematic approach to literature-guided biomarker discovery. AVAILABILITY AND IMPLEMENTATION: We developed a two-stage computational framework that combines LLM-based screening with literature validation for systematic gene prioritization. Starting with 10 824 genes from the BloodGen3 repertoire, we applied multi-criteria evaluation for sepsis relevance, followed by retrieval-augmented generation using 6346 curated sepsis publications. A novel faithfulness evaluation system verified that LLM predictions aligned with retrieved literature evidence. Source code and implementation details are available at https://github.com/taushifkhan/llm-geneprioritization-framework, vector database at https://doi.org/10.5281/zenodo.15802241, and Interactive demonstration at https://llm-geneprioritization.streamlit.app/.

Humans↗
PubMed2001

A formal framework for modelling and validating medical systems.

Medical computerised systems which have a major effect on human lives (e.g. those used for diagnosis, therapy, surgery, in the intensive care units, etc) are considered as safety critical systems. Such systems are sometimes responsible for major damages and injuries due to unpredicted malfunction. Misleading user requirements, errors in the specification and in the implementation are the usual reasons responsible for non-safe systems. This paper advocates the use of an integrated formal framework based on a computational machine (X-Machine), in the development of safety critical medical systems. This formal framework gives the ability to intuitively as well as formally model a system, then automatically check if the produced model has all the desired properties, and finally test if the implementation is equivalent to the specification by applying a complete set of test cases. Therefore, the use of this framework in the development of systems in safety critical medical domains can assure that the final product is valid with respect to the user requirements by revealing errors during the whole development life cycle and subsequently add to the confidence of their use. The proposed framework is accompanied by an example, which demonstrates the use of X-Machines in specification, testing and verification.

Medical Informatics↗
PubMed2003

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Animals↗
PubMedDate not supplied

A framework for analyzing the cognitive complexity of computer-assisted clinical ordering.

Computer-assisted provider order entry is a technology that is designed to expedite medical ordering and to reduce the frequency of preventable errors. This paper presents a multifaceted cognitive methodology for the characterization of cognitive demands of a medical information system. Our investigation was informed by the distributed resources (DR) model, a novel approach designed to describe the dimensions of user interfaces that introduce unnecessary cognitive complexity. This method evaluates the relative distribution of external (system) and internal (user) representations embodied in system interaction. We conducted an expert walkthrough evaluation of a commercial order entry system, followed by a simulated clinical ordering task performed by seven clinicians. The DR model was employed to explain variation in user performance and to characterize the relationship of resource distribution and ordering errors. The analysis revealed that the configuration of resources in this ordering application placed unnecessarily heavy cognitive demands on the user, especially on those who lacked a robust conceptual model of the system. The resources model also provided some insight into clinicians' interactive strategies and patterns of associated errors. Implications for user training and interface design based on the principles of human-computer interaction in the medical domain are discussed.

Cognition↗
PubMed1994

A framework for "Need to Know" authorizations in medical computer systems: responding to the constitutional requirements.

"Need to Know" systems which restrict access to computerized data to those with a specified need for the data have been described as part of the solution to the problem of privacy in health care information systems. However, no operational "need to know" system is described in the medical literature. Recent legal developments in constitutional privacy protection make a "need to know" system mandatory, not optional. In sophisticated information systems users can utilize the unique characteristics of the system itself to implement a high level "need to know" system, based on the institution's own patient treatment pattern. This article provides an analytical tool for helping to define a "need to know" system with reference to the specific problems of health care institutions.

Civil Rights↗
PubMed2002

Clinical experience of CNC-milled titanium frameworks supported by implants in the edentulous jaw: a 3-year interim report.

BACKGROUND: The use of computer numeric controlled (CNC)-milled titanium frameworks is a new technique for framework fabrication, and few clinical reports have been made on this treatment modality. PURPOSE: The goal of this study was to report the clinical performance of implant-supported prostheses with CNC-milled titanium frameworks in the edentulous jaw and to compare the results with prostheses provided with conventional cast frameworks during the first 3 years of function. MATERIALS AND METHODS: A consecutive group of 126 edentulous patients were provided by random distribution with 67 prostheses with CNC-milled titanium frameworks in 23 upper and 44 lower jaws and 62 conventional prostheses with gold-alloy castings in 31 upper and 31 lower jaws. Radiographic 1-year data and clinical 3-year data were collected for both the titanium and control group. RESULTS: One prosthesis was lost in each group owing to loss of implants, and the overall 3-year prosthesis cumulative survival rate was 98.2% for both groups. Patients with smoking habits experienced significantly more implant failures than nonsmokers (p =.006). Few problems were observed. No metal fractures were seen in the test group, whereas two frameworks and one abutment screw fractured in the control group. Resin veneer fractures were the most common complication, with a slightly higher incidence observed in the control group. CONCLUSIONS: Computer numeric controlled-milled titanium frameworks can be used as an alternative to conventional castings in the edentulous jaw, presenting clinical performance similar to that of conventional cast frameworks during the first 3 years of function. key words: computer numeric controlled, implant supported, prostheses, titanium

Computer-Aided Design↗
PubMed2004

Computational modeling of healing: an application of the material force method.

The basic aim of the present contribution is the qualitative simulation of healing phenomena typically encountered in hard and soft tissue mechanics. The mechanical framework is provided by the theory of open system thermodynamics, which will be formulated in the spatial as well as in the material motion context. While the former typically aims at deriving the density and the spatial motion deformation field in response to given spatial forces, the latter will be applied to determine the material forces in response to a given density and material deformation field. We derive a general computational framework within the finite element context that will serve to evaluate both the spatial and the material motion problem. However, once the spatial motion problem has been solved, the solution of the material motion problem represents a mere post-processing step and is thus extremely cheap from a computational point of view. The underlying algorithm will be elaborated systematically by means of two prototype geometries subjected to three different representative loading scenarios, tension, torsion, and bending. Particular focus will be dedicated to the discussion of the additional information provided by the material force method. Since the discrete material node point forces typically point in the direction of potential material deposition, they can be interpreted as a driving force for the healing mechanism.

Animals↗
PubMed2004

A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects.

Multiple factors simultaneously affect the spiking activity of individual neurons. Determining the effects and relative importance of these factors is a challenging problem in neurophysiology. We propose a statistical framework based on the point process likelihood function to relate a neuron's spiking probability to three typical covariates: the neuron's own spiking history, concurrent ensemble activity, and extrinsic covariates such as stimuli or behavior. The framework uses parametric models of the conditional intensity function to define a neuron's spiking probability in terms of the covariates. The discrete time likelihood function for point processes is used to carry out model fitting and model analysis. We show that, by modeling the logarithm of the conditional intensity function as a linear combination of functions of the covariates, the discrete time point process likelihood function is readily analyzed in the generalized linear model (GLM) framework. We illustrate our approach for both GLM and non-GLM likelihood functions using simulated data and multivariate single-unit activity data simultaneously recorded from the motor cortex of a monkey performing a visuomotor pursuit-tracking task. The point process framework provides a flexible, computationally efficient approach for maximum likelihood estimation, goodness-of-fit assessment, residual analysis, model selection, and neural decoding. The framework thus allows for the formulation and analysis of point process models of neural spiking activity that readily capture the simultaneous effects of multiple covariates and enables the assessment of their relative importance.

Action Potentials↗
PubMed2026

Recent Advances in Multi-Omics of Systemic Lupus Erythematosus.

This comprehensive narrative review examines recent advances in multi-omics research for Systemic Lupus Erythematosus (SLE), emphasizing integrated approaches over single-omics studies. The review critically evaluates technological advancements, methodological innovations, and clinical applications while identifying current limitations and future research directions. We conducted a comprehensive narrative review following SANRA guidelines, searching PubMed, Web of Science, Scopus, and Embase, covering publications from January 2018 to June 2025. The review focuses on studies integrating two or more omics layers in SLE research, with emphasis on computational methods, biomarker validation, and clinical applications. Multi-omics integration has revealed critical insights into SLE pathogenesis, including immune cell heterogeneity, gene-environment interactions, and metabolic dysregulation. However, significant challenges remain in data integration methodologies, small sample sizes, and biomarker reproducibility. Current computational approaches include early integration (concatenation), intermediate integration (joint dimensionality reduction), and late integration (ensemble methods). While multi-omics approaches offer unprecedented insights into SLE complexity, standardized integration protocols and robust validation frameworks are urgently needed. Small sample sizes and heterogeneity issues limit reproducibility, particularly affecting biomarker discovery and clinical translation. Multi-omics integration represents a paradigm shift toward precision medicine in SLE, but realizing this potential requires addressing current methodological limitations, standardizing validation processes, and developing robust computational frameworks for reliable clinical applications.

Humans↗
PubMed1986

A theoretical study of the comparative binding affinities of daunomycin derivatives to a double-stranded oligomeric DNA. Proposal for new high affinity derivatives.

Theoretical computations were performed on the comparative binding affinities of daunomycin (DM, 1) and seven derivatives related to the double-stranded oligonucleotide d(CGATCG)2. The compounds investigated were 4-demethoxy DM (2), and its beta-anomer (3), 4-demethoxy-7,9-bis-epi DM (4) and its beta anomer (5), a derivative with glucosamine instead of daunosamine (6), and two additional hypothetical DM derivatives in which the cationic NH3+ group of the daunosamine moiety is replaced by either a CH2--NH3+ group (7) or a CH2CH2NH3+ group (8), so as to indicate the effect on the binding affinity of interposing one- or two-methylene groups between the sugar and the cationic charge. The conformational angles of the hexanucleotide are fixed in values found in the representative crystal structure of the d(CGTACG)2-DM complex. The intermolecular drug-hexanucleotide interaction energies and the conformational energy changes of the drug upon binding are computed and optimized in the framework of the SIBFA procedure (sum of interactions between fragments computed ab initio), which uses empirical formulas based on ab initio SCF computations. The overall binding affinity ordering of compounds 1-6 compares satisfactorily with the ordering of available experimental affinity constants. The binding affinities of compounds 7 and 8, for which no experimental results seem to be available yet, are predicted to be significantly higher than those of the parent compound DM, with the greatest affinity found for 7. Because of the overall correlation between binding affinity of anthracyclines to DNA and their antitumor activity, these last two compounds deserve an exploration of their chemotherapeutic efficiency.

DNA↗
PubMed1998

Computational models of neuromodulation.

Computational modeling of neural substrates provides an excellent theoretical framework for the understanding of the computational roles of neuromodulation. In this review, we illustrate, with a large number of modeling studies, the specific computations performed by neuromodulation in the context of various neural models of invertebrate and vertebrate preparations. We base our characterization of neuromodulations on their computational and functional roles rather than on anatomical or chemical criteria. We review the main framework in which neuromodulation has been studied theoretically (central pattern generation and oscillations, sensory processing, memory and information integration). Finally, we present a detailed mathematical overview of how neuromodulation has been implemented at the single cell and network levels in modeling studies. Overall, neuromodulation is found to increase and control computational complexity.

Animals↗