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Path-level interpretation of Gaussian graphical models using the pair-path subscore
BackgroundConstruction of networks from cross-sectional biological data is increasingly common. Many recent methods have been based on Gaussian...
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GMMchi: gene expression clustering using Gaussian mixture modeling
BackgroundCancer evolution consists of a stepwise acquisition of genetic and epigenetic changes, which alter the gene expression profiles of cells in...
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Probabilistic Graphical Models for Gene Regulatory Networks
The advancement of technologies has generated high-throughput data of diverse biological entities, such as messenger RNAs (mRNAs), proteins, and...
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Clustering of atoms relative to vector space in the Z-matrix coordinate system and ‘graphical fingerprint’ analysis of 3D pharmacophore structure
The behavior of a molecule within its environment is governed by chemical fields present in 3D space. However, beyond local descriptors in 3D, the...
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Reviewing and improving spatiotemporal modeling approaches for mackerel’s total annual egg production
Since the late 1970s the international ICES mackerel egg survey takes place in the Northeast Atlantic to obtain an estimate of total annual egg...
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CryoREAD: de novo structure modeling for nucleic acids in cryo-EM maps using deep learning
DNA and RNA play fundamental roles in various cellular processes, where their three-dimensional structures provide information critical to...
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Quantitative Imaging Analysis of NF-κB for Mathematical Modeling Applications
Mathematical models can integrate different types of experimental datasets, reconstitute biological systems in silico, and identify previously...
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Proteochemometrics modeling for prediction of the interactions between caspase isoforms and their inhibitors
Caspases (cysteine-aspartic proteases) play critical roles in inflammation and the programming of cell death in the form of necroptosis, apoptosis,...
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SHARE-Topic: Bayesian interpretable modeling of single-cell multi-omic data
Multi-omic single-cell technologies, which simultaneously measure the transcriptional and epigenomic state of the same cell, enable understanding...
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First report of q-RASAR modeling toward an approach of easy interpretability and efficient transferability
Quantitative structure–activity relationship (QSAR) and read-across techniques have recently been merged into a new emerging field of read-across...
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Recent developments in modeling, imaging, and monitoring of cardiovascular diseases using machine learning
Cardiovascular diseases are the leading cause of mortality, morbidity, and hospitalization around the world. Recent technological advances have...
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Hidden Markov modeling for maximum probability neuron reconstruction
Recent advances in brain clearing and imaging have made it possible to image entire mammalian brains at sub-micron resolution. These images offer the...
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Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast
ContextTidal saline wetlands (TSWs) are highly threatened from climate-change effects of sea-level rise. Studies of TSWs along the East Coast U.S....
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PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling
BackgroundComputational methods based on initial screening and prediction of peptides for desired functions have proven to be effective alternatives...
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Artificial Neural Network Models for Rainfall-Runoff Modeling in India: Studies From the Kolar and Kuttiyadi River Watersheds
The last two decades have observed an increased usage of artificial neural networks (ANNs) for assessing and forecasting water resource parameters,...
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Stochastic Modeling of Effects Exercised by Protective Forest Strips: The Cauchy Distribution
AbstractThe dynamics of natural objects in space and time is closely related to their stochastic behavior determined by climatic and anthropogenic...
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A metabolic modeling platform for the computation of microbial ecosystems in time and space (COMETS)
Genome-scale stoichiometric modeling of metabolism has become a standard systems biology tool for modeling cellular physiology and growth. Extensions...
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Probing the molecular mechanisms of α-synuclein inhibitors unveils promising natural candidates through machine-learning QSAR, pharmacophore modeling, and molecular dynamics simulations
Parkinson’s disease is characterized by a multifactorial nature that is linked to different pathways. Among them, the abnormal deposition and...
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Exploring the effects of temperature on demersal fish communities in the Central Mediterranean Sea using INLA-SPDE modeling approach
Climate change significantly impacts marine ecosystems worldwide, leading to alterations in the composition and structure of marine communities. In...
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Graph Theory-Based Approach in Brain Connectivity Modeling and Alzheimer’s Disease Detection
There is strong evidence that the pathological findings of Alzheimer’s disease (AD), consisting of accumulated amyloid plaques and neurofibrillary...