AIMC Topic: Models, Immunological

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Intelligent solution predictive networks for non-linear tumor-immune delayed model.

Computer methods in biomechanics and biomedical engineering Jun 23, 2023
In this article, we analyze the dynamics of the non-linear tumor-immune delayed (TID) model illustrating the interaction among tumor cells and the immune system (cytotoxic T lymphocytes, T helper cells), where the delays portray the times required fo...
Neural Networks, Computer Neoplasms Models, Biological Nonlinear Dynamics Models, Immunological Humans
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Literature Mining and Mechanistic Graphical Modelling to Improve mRNA Vaccine Platforms.

Frontiers in immunology Sep 7, 2021
RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine development, showing strong immunogenicity and an overall favorable safety profile. While preclinical testin...
mRNA Vaccines Vaccine Development Systems Biology Natural Language Processing Data Mining Computer Graphics Models, Immunological Translational Research, Biomedical Knowledge Bases Humans Animals
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Pseudocell Tracer-A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombination.

PLoS computational biology May 3, 2021
Single cell RNA sequencing (scRNAseq) can be used to infer a temporal ordering of cellular states. Current methods for the inference of cellular trajectories rely on unbiased dimensionality reduction techniques. However, such biologically agnostic or...
Databases, Nucleic Acid Models, Immunological Receptors, Cytokine Recombination, Genetic Basic-Leucine Zipper Transcription Factors Mice, Inbred C57BL Gene Expression B-Lymphocytes Supervised Machine Learning Immunoglobulin Class Switching Interleukin-4 NF-kappa B p50 Subunit Immunoglobulin G STAT6 Transcription Factor Computer Simulation Animals Neural Networks, Computer Mice Single-Cell Analysis Computational Biology RNA-Seq Signal Transduction
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A Machine Learning Approach Yields a Multiparameter Prognostic Marker in Liver Cancer.

Cancer immunology research Jan 11, 2021
A number of staging systems have been developed to predict clinical outcomes in hepatocellular carcinoma (HCC). However, no general consensus has been reached regarding the optimal model. New approaches such as machine learning (ML) strategies are po...
Female Risk Factors Young Adult Adult T-Lymphocytes Humans Machine Learning Prognosis Retrospective Studies Liver Neoplasms Carcinoma, Hepatocellular Venous Thrombosis Neoplasm Invasiveness Liver Male Middle Aged Risk Assessment Adolescent Kaplan-Meier Estimate Models, Immunological Immune Checkpoint Proteins Neoplasm Staging Hepatectomy Portal Vein Lymphocyte Count
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Analysis of defective pathways and drug repositioning in Multiple Sclerosis via machine learning approaches.

Computers in biology and medicine Oct 9, 2019
BACKGROUND: Although some studies show that there could be a genetic predisposition to develop Multiple Sclerosis (MS), attempts to find genetic signatures related to MS diagnosis and development are extremely rare.
Databases, Nucleic Acid Models, Immunological Metabolic Networks and Pathways Humans Multiple Sclerosis Machine Learning Gene Expression Regulation Male Oligonucleotide Array Sequence Analysis Retrospective Studies Signal Transduction Female Drug Repositioning
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Towards the development of robot immune system: A combined approach involving innate immune cells and T-lymphocytes.

Bio Systems Aug 10, 2018
Mobile robots in uncertain and unstructuredenvironments frequently encounter faults. Therefore, an effective fault detection and recovery mechanism is required. One can possibly investigate natural systems to seek inspiration to develop systems that ...
Equipment Failure Analysis Models, Immunological Computer Simulation T-Lymphocytes Immunity, Innate Robotics Humans Biomimetics Artificial Intelligence Software Algorithms
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Computational Intelligence for Medical Imaging Simulations.

Journal of medical systems Nov 25, 2017
This paper describes how to simulate medical imaging by computational intelligence to explore areas that cannot be easily achieved by traditional ways, including genes and proteins simulations related to cancer development and immunity. This paper ha...
Humans Artificial Intelligence Algorithms Computer Simulation Diagnostic Imaging Models, Biological Models, Immunological Models, Genetic Proteins
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and cell-based analyses reveal strong divergence between prediction and observation of T-cell-recognized tumor antigen T-cell epitopes.

The Journal of biological chemistry May 23, 2017
Tumor exomes provide comprehensive information on mutated, overexpressed genes and aberrant splicing, which can be exploited for personalized cancer immunotherapy. Of particular interest are mutated tumor antigen T-cell epitopes, because neoepitope-s...
Melanoma Reproducibility of Results Mice, Transgenic Animals Cancer Vaccines Computational Biology Models, Immunological Humans Peptide Fragments Antigens, Neoplasm Protein Refolding Neoplasm Proteins Artificial Intelligence Epitopes Vaccines, Synthetic Protein Stability Mice, Knockout Cells, Cultured T-Lymphocytes, Cytotoxic HLA-A2 Antigen Membrane Proteins Expert Systems Oligopeptides Immunogenicity, Vaccine
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Immunological Approach for Full NURBS Reconstruction of Outline Curves from Noisy Data Points in Medical Imaging.

IEEE/ACM transactions on computational biology and bioinformatics Mar 28, 2017
Curve reconstruction from data points is an important issue for advanced medical imaging techniques, such as computer tomography (CT) and magnetic resonance imaging (MRI). The most powerful fitting functions for this purpose are the NURBS (non-unifor...
Models, Immunological Brain Humans Artificial Intelligence Image Processing, Computer-Assisted Algorithms Diagnostic Imaging
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A Novel Hybrid Clonal Selection Algorithm with Combinatorial Recombination and Modified Hypermutation Operators for Global Optimization.

Computational intelligence and neuroscience Sep 8, 2016
Artificial immune system is one of the most recently introduced intelligence methods which was inspired by biological immune system. Most immune system inspired algorithms are based on the clonal selection principle, known as clonal selection algorit...
Cloning, Molecular Animals Immune System Humans Models, Genetic Models, Immunological Artificial Intelligence Mutation Algorithms Biomimetics Computer Simulation
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