This chapter explores the integration of omics and bioinformatics for Parkinson's disease (PD) diagnosis and potential cure discovery. It begins with an overview of PD and its prevalence, followed by an examination of key mutations in genes linked to the disease. These mutations lead to dysfunctional proteins, triggering PD progression. The chapter delves into techniques like whole-exome sequencing (WES), genome-wide association sequencing (GWAS), and whole-genome sequencing (WGS). These methods enable the exploration of omics levels such as lipidomics, metabolomics, genomics, and proteomics

Antimicrobial resistance (AMR) is one of the threats to our world according to the World Health Organization (WHO). Resistance is an evolutionary dynamic process where host-associated microbes have to adapt to their stressful environments. AMR could be classified according to the mechanism of resistance or the biome where resistance takes place. Antibiotics are one of the stresses that lead to resistance through antibiotic resistance genes (ARGs). The resistome could be defined as the collection of all ARGs in an organism’s genome or metagenome. Currently, there is a growing body of evidence

Biomedical research and pharmaceutical development have been profoundly impacted by genomics in recent years, with researchers gaining new understanding of the genetic pathways underlying disease and opening up new opportunities for the creation of targeted therapeutic interventions. Without a comprehensive grasp of the genetic mechanisms at play, medication discovery approaches in the past often relied on trial and error, targeting particular symptoms or pathways. However, the advent of genomics has changed the game. Scientific advances in high-throughput DNA sequencing have allowed

Image segmentation is considered one of the essen-tial tasks for extracting useful information from an image. Given the brain tumor and its consumption of medical resources, the development of a deep learning method for MRI to segment the brain tumor of patients’ MRI is illustrated here. Brain tumor segmentation technique is crucial in detecting and treating MRI brain tumors. Furthermore, it assists physicians in locating and measuring tumors and developing treatment and rehabilitation programs. The residual U-Net++ encoder-decoder-based architec-ture is designed as the primary network, and it

There are many novel techniques for intrusion detection in vehicular ad hoc networks and autonomous and connected vehicles. Detecting and reporting an attack is the main responsibility of an Intrusion detection system (IDS). Deep learning is used to make IDS smarter and more accurate. It implies other challenges on the other hand. This paper covers the proposed IDS based deep learning solutions and comparing effectiveness and efficiency of those solutions. © 2022 IEEE.

Many systems have recently begun to examine blockchain qualities in order to create cooperation enforcement methods. This paper provides a complete and extensive evaluation of work on multi-hop MANETs with blockchain-based trust control between nodes. We contextualize the snag of security in MANETs resulting from the lack of trust between the participating nodes. We present the blockchain concepts and discuss the limitation of the current blockchain in MANETs. We review the promising proposed ideas in the state-of-the-art based on research papers. Finally, we discuss and summarize strategies

Background: Hepatocellular carcinoma (HCC) is the most common primary liver cancer. Chronic hepatitis and liver cirrhosis lead to accumulation of genetic alterations driving HCC pathogenesis. This study is designed to explore genomic landscape of HCC in Egyptian patients by whole exome sequencing. Methods: Whole exome sequencing using Ion Torrent was done on 13 HCC patients, who underwent surgical intervention (7 patients underwent living donor liver transplantation (LDLT) and 6 patients had surgical resection}. Results: Mutational signature was mostly S1, S5, S6, and S12 in HCC. Analysis of

Big Data Stream processing engines such as Apache Flink use windowing techniques to handle unbounded streams of events. Gathering all pertinent input within a window is crucial for event-time windowing since it affects how accurate results are. A significant part of this process is played by watermarks, which are unique timestamps that show the passage of events in time. However, the current watermark generation method in Apache Flink, which works at the level of the input stream, tends to favor faster sub-streams, resulting in dropped events from slower sub-streams. In our analysis, we found

The Funding section in the original version of this Article was incomplete. “This work received funding from the European Union’s 2020 research and innovation programme under Grant Agreement No. 825903 (euCanSHare project), as well as from the Spanish Ministry of Science, Innovation and Universities under grant agreement RTI2018-099898-B-I00. Additionally, the research leading to these results has received funding from Cerebra Foundation for the Brain Injured Child (Carmarthen, Wales, UK).” now reads: “This work received funding from the European Union’s 2020 research and innovation programme

There are many situations where there is a need for certain devices to be connected in a network independently without having a heavy infrastructure or human interventions to configure and connect them. This type of network is called ad-hoc networks. The key concern with such networks is how nodes communicate with each other and exchange information efficiently and securely. The issue with ad hoc networks is that traditional routing protocols are not suitable for such networks. In this paper, the performance of specific routing protocols for ad hoc networks will be evaluated. © 2022 IEEE.