AIMC Topic: Systems Biology

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Systems Biology and Machine Learning in Plant-Pathogen Interactions.

Molecular plant-microbe interactions : MPMI
Systems biology is an inclusive approach to study the static and dynamic emergent properties on a global scale by integrating multiomics datasets to establish qualitative and quantitative associations among multiple biological components. With an abu...

PISTON: Predicting drug indications and side effects using topic modeling and natural language processing.

Journal of biomedical informatics
The process of discovering novel drugs to treat diseases requires a long time and high cost. It is important to understand side effects of drugs as well as their therapeutic effects, because these can seriously damage the patients due to unexpected a...

Initial state perturbations as a validation method for data-driven fuzzy models of cellular networks.

BMC bioinformatics
BACKGROUND: Data-driven methods that automatically learn relations between attributes from given data are a popular tool for building mathematical models in computational biology. Since measurements are prone to errors, approaches dealing with uncert...

Unsupervised, Statistically Based Systems Biology Approach for Unraveling the Genetics of Complex Traits: A Demonstration with Ethanol Metabolism.

Alcoholism, clinical and experimental research
BACKGROUND: A statistical pipeline was developed and used for determining candidate genes and candidate gene coexpression networks involved in 2 alcohol (i.e., ethanol [EtOH]) metabolism phenotypes, namely alcohol clearance and acetate area under the...

Using Emulation to Engineer and Understand Simulations of Biological Systems.

IEEE/ACM transactions on computational biology and bioinformatics
Modeling and simulation techniques have demonstrated success in studying biological systems. As the drive to better capture biological complexity leads to more sophisticated simulators, it becomes challenging to perform statistical analyses that help...

A portable structural analysis library for reaction networks.

Bio Systems
The topology of a reaction network can have a significant influence on the network's dynamical properties. Such influences can include constraints on network flows and concentration changes or more insidiously result in the emergence of feedback loop...

Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB).

BMC bioinformatics
BACKGROUND: Recent cancer genome studies on many human cancer types have relied on multiple molecular high-throughput technologies. Given the vast amount of data that has been generated, there are surprisingly few databases which facilitate access to...

A flexible ontology for inference of emergent whole cell function from relationships between subcellular processes.

Scientific reports
Whole cell responses arise from coordinated interactions between diverse human gene products functioning within various pathways underlying sub-cellular processes (SCP). Lower level SCPs interact to form higher level SCPs, often in a context specific...

Generative models for network neuroscience: prospects and promise.

Journal of the Royal Society, Interface
Network neuroscience is the emerging discipline concerned with investigating the complex patterns of interconnections found in neural systems, and identifying principles with which to understand them. Within this discipline, one particularly powerful...

Meta-Path Methods for Prioritizing Candidate Disease miRNAs.

IEEE/ACM transactions on computational biology and bioinformatics
MicroRNAs (miRNAs) play critical roles in regulating gene expression at post-transcriptional levels. Numerous experimental studies indicate that alterations and dysregulations in miRNAs are associated with important complex diseases, especially cance...