AIMC Topic: Systems Biology
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Combined mechanistic modeling and machine-learning approaches in systems biology - A systematic literature review.
Computer methods and programs in biomedicine
Jun 17, 2023
BACKGROUND AND OBJECTIVE: Mechanistic-based Model simulations (MM) are an effective approach commonly employed, for research and learning purposes, to better investigate and understand the inherent behavior of biological systems. Recent advancements ...
Modulating autophagy to treat diseases: A revisited review on in silico methods.
Journal of advanced research
May 14, 2023
BACKGROUND: Autophagy refers to the conserved cellular catabolic process relevant to lysosome activity and plays a vital role in maintaining the dynamic equilibrium of intracellular matter by degrading harmful and abnormally accumulated cellular comp...
A decision support system based on artificial intelligence and systems biology for the simulation of pancreatic cancer patient status.
CPT: pharmacometrics & systems pharmacology
Mar 31, 2023
Oncology treatments require continuous individual adjustment based on the measurement of multiple clinical parameters. Prediction tools exploiting the patterns present in the clinical data could be used to assist decision making and ease the burden a...
Metabolic engineering for sustainability and health.
Trends in biotechnology
Jan 10, 2023
Bio-based production of chemicals and materials has attracted much attention due to the urgent need to establish sustainability and enhance human health. Metabolic engineering (ME) allows purposeful modification of cellular metabolic, regulatory, and...
Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 8, 2022
Approximate Bayesian Computation is widely used in systems biology for inferring parameters in stochastic gene regulatory network models. Its performance hinges critically on the ability to summarize high-dimensional system responses such as time ser...
Multi-omics disease module detection with an explainable Greedy Decision Forest.
Scientific reports
Oct 7, 2022
Machine learning methods can detect complex relationships between variables, but usually do not exploit domain knowledge. This is a limitation because in many scientific disciplines, such as systems biology, domain knowledge is available in the form ...
Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.
International journal of molecular sciences
Sep 8, 2022
In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identify some important biomarkers as drug targets. Further, a systematic drug discovery method with a dee...
Unsupervised and semi-supervised learning: the next frontier in machine learning for plant systems biology.
The Plant journal : for cell and molecular biology
Jul 27, 2022
Advances in high-throughput omics technologies are leading plant biology research into the era of big data. Machine learning (ML) performs an important role in plant systems biology because of its excellent performance and wide application in the ana...
Current progress and open challenges for applying deep learning across the biosciences.
Nature communications
Apr 1, 2022
Deep Learning (DL) has recently enabled unprecedented advances in one of the grand challenges in computational biology: the half-century-old problem of protein structure prediction. In this paper we discuss recent advances, limitations, and future pe...
Predicting deleterious missense genetic variants via integrative supervised nonnegative matrix tri-factorization.
Scientific reports
Dec 9, 2021
Among an assortment of genetic variations, Missense are major ones which a small subset of them may led to the upset of the protein function and ultimately end in human diseases. Various machine learning methods were declared to differentiate deleter...
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