Background: Oncolytic viral therapy is known as a new promising strategy to treat cancer.Oncolyticviruses (OVs) can replicate in cancer cells, and besides this primary effect, OVs can also stimulate the immune system.Moreover, Adenovirus serotype 5 (Ad5) is widely used as an oncolytic agent for cancer therapy.The present study aimed to make a chang
The ubiquitous availability of genome sequencing data explains the popularity of machine learning-based methods for the prediction of protein properties from their amino acid sequences.Over the years, while revising our own work, reading submitted manuscripts as well as published papers, we have noticed several recurring issues, which make some rep
The aim of this paper is to present the general characteristics of the individual-based models (IbMs), and the bar drain board way to deal with them when a bio system, a set of discrete life entities evolving in a changing environment, is modeled.A discussion of the advantages and disadvantages that this type of discrete modeling has compared with
The Canopy Live Fuel Moisture Content (LFMC) is a pivotal factor in wildfire risk assessment within the fire triangle model, representing the ratio of canopy moisture content to its dry weight.Against the backdrop of degraded Moderate Resolution Imaging Spectroradiometer (MODIS) performance and the underutilization of Visible Infrared Imaging Radio
Active learning aims at obtaining high-accuracy models with as a few labeled data as possible, by iteratively and elaborately selecting most valuable data to query labels during the learning process, thereby the cost of labeling data can be reduced.Most previous active learning approaches consider the situation of centralized processing, where all