Artificial intelligence-driven reverse vaccinology for vaccine: Prioritizing epitope-based candidates.

is the causative agent of the sexually transmitted disease gonorrhea. The increasing prevalence of this disease worldwide, the rise of antibiotic-resistant strains, and the difficulties in treatment necessitate the development of a vaccine, highlighting the significance of preventative measures to control and eradicate the infection. Currently, there is no widely available vaccine, partly due to the bacterium's ability to evade natural immunity and the limited research investment in gonorrhea compared to other diseases.

Machine Learning and Artificial Intelligence: A Paradigm Shift in Big Data-Driven Drug Design and Discovery.

Background: The lengthy and expensive process of developing a novel medicine often takes many years and entails a significant financial burden due to its poor success rate. Furthermore, the processing and analysis of quickly expanding massive data necessitate the use of cutting-edge methodologies. As a result, Artificial Intelligence-driven methods that have been shown to improve the efficiency and accuracy of drug discovery have grown in favor.

A novel sequence space related to [Formula: see text] defined by Orlicz function with application in pattern recognition.

In the field of pattern recognition, clustering groups the data into different clusters on the basis of similarity among them. Many a time, the similarity level between data points is derived through a distance measure; so, a number of clustering techniques reliant on such a measure are developed. Clustering algorithms are modified by employing an appropriate distance measure due to the high versatility of a data set.

Sequence spaces [Formula: see text] and [Formula: see text] with application in clustering.

Distance measures play a central role in evolving the clustering technique. Due to the rich mathematical background and natural implementation of [Formula: see text] distance measures, researchers were motivated to use them in almost every clustering process. Beside [Formula: see text] distance measures, there exist several distance measures.

ViralEpi v1.0: a high-throughput spectrum of viral epigenomic methylation profiles from diverse diseases.

Aims: To develop a computational resource for viral epigenomic methylation profiles from diverse diseases.

Materials & Methods: Methylation patterns of Epstein-Barr virus and hepatitis B virus genomic regions are provided as web platform developed using open source Linux-Apache-MySQL-PHP (LAMP) bundle: programming and scripting languages, that is, HTML, JavaScript and PERL.

Results: A comprehensive and integrated web resource ViralEpi v1.