In this paper, we proposed an improved method for the classification of SCZ and HC based on individual hierarchical brain networks constructed from structural MRI images. Our method involves constructing individual hierarchical networks…
In multi-cellular organisms, molecular signaling spans multiple distance scales and is essential to tissue structure and functionality. Molecular communications is increasingly researched and developed as a key subsystem in the Internet-of-Nano-Things paradigm.
There are many obstacles in the transport of chemotherapeutic drugs to tumor cells that lead to irregular and non-uniform uptake of drugs inside tumors. The study of these transport problems will help with accurate prediction of drug transport and optimizing treatment strategy.
Nanosized devices operating inside the human body open up new prospects in the healthcare domain. Invivo wireless nanosensor networks (iWNSNs) will result in a plethora of applications ranging from intrabody health-monitoring to drug-delivery systems.
Cell mechanics is a novel label-free biomarker for indicating cell states and pathological changes. The advent of atomic force microscopy (AFM) provides a powerful tool for quantifying the mechanical properties of single living cells in aqueous conditions.
In this paper, we analyze molecular communications (MCs) in a proposed artificial synapse (AS), whose main difference from biological synapses (BSs) is that it is closed, i.e., transmitter molecules cannot diffuse out from AS.
Bioinformatics and biomedicine research is fundamental to our understanding of complex biological systems, impacting the science and technology of fields ranging from agricultural and environmental sciences to pharmaceutical and medical sciences.
Complex networks are ubiquitous in nature. In biological systems, biomolecules interact with each other to form so-called biomolecular networks, which determine the cellular behaviors of living organisms.
In ultrasound image analysis, the speckle tracking methods are widely applied to study the elasticity of body tissue. However, “feature-motion decorrelation” still remains as a challenge for the speckle tracking methods.
High dimensionality has become a typical feature of biomolecular data. In this paper, a novel dimension reduction method named p-norm singular value decomposition (PSVD) is proposed to seek the low-rank approximation matrix to the biomolecular data.