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.
This paper reports a novel electrochemical method for detection of Glutathione (GSH) using Glutathione-S-Transferase (GST) – ZnO composite nanoparticles to investigate the prospects of the method for detection of cancer at an early stage.
Many recent efforts have been made for the development of machine learning based methods for fast and accurate phosphorylation site prediction. Currently, a majority of well-performing methods are based on hybrid information to build prediction models, such as evolutionary information, and disorder information, etc.
Understanding the fundamentals of communication among neurons, known as neuro-spike communication, leads to reach bio-inspired nanoscale communication paradigms. In this work, we focus on a part of neuro-spike communication, known as axonal transmission, and propose a realistic model for it
To maximize the effect of treatment and minimize the adverse effect on patients, we propose to optimize nanorobots-assisted targeted drug delivery (TDD) for locoregional treatment of tumor from the perspective of touchable communication channel estimation and waveform design.
A nano-abnormality detection scheme (NADS) in molecular nano-networks is studied. This is motivated by the fact that early detection of diseases such as cancer plays a crucial role in their successful treatment.
The use of echogenic liposomes to deliver chemotherapeutic agents for cancer treatment has gained wide recognition in the last 20 years. Cancerous cells can develop multiple drug resistance (MDR), in part, due to the drop in concentration of chemotherapeutic agents below the therapeutic levels inside the tumor.