As the amount of data being sent has risen dramatically in recent years; protecting that data has become increasingly important. Cryptography is the process of transforming plain text messages into ones that can no longer be decoded. An information security system's algorithm for encrypting and decrypting data cannot function without them. Data transmission via a communication network can benefit greatly from the use of encryption. Short message service (SMS) is still popular despite the availability of several online messaging platforms. Despite this, these services can be easily cracked, making SMS less secure for transferring critical information. The usage of appropriate cryptographic algorithms is essential to ensuring the safety of your data. Cryptanalysis and pattern prediction are better protected. This study uses a hybridized version of the Vigenère cipher with AES. In tests, the Vigenère-AES came out on top, and it may be used to keep sensitive data safe from prying eyes.

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With the advancement of network and multimedia technologies in recent years, multimedia data, particularly picture, audio, and video data, has become increasingly frequently used in human civilization. Some multimedia data, such as entertainment, politics, economics, militaries, industries, and education, requires secrecy, integrity, and ownership or identity protection. Cryptology, which looks to be a viable method for information security, has been used in many practical applications to safeguard multimedia data in this regard. Traditional ciphers based on number theory or algebraic ideas, such as data encryption standard (DES), advanced encryption standard (AES), and other similar algorithms, which are most commonly employed for text or binary data, do not appear to be appropriate for multimedia applications. As a result, this research examines effective algorithms for data security.

Motivation Post-GWAS analysis is designed to decipher the functional consequences of significant Single Nucleotide Polymorphisms (SNP) in the era of Genome Wide Association Studies (GWAS). This can be translated into research insights and clinical benefits such as effectiveness of strategies for disease screening, treatment and prevention. However, the setup of post-GWAS (pGWAS) tools can be quite complicated and it mostly requires big data. The challenge however is, scientists are required to have sufficient experience with several of these technically complex and complicated tools in order to complete the pGWAS analysis. Results We present SysBiolPGWAS, a post-GWAS web application that provides a comprehensive functionality for biologists and non-bioinformaticians to conduct several post-GWAS analyses to overcome the above challenges. It provides unique functionalities for analysis involving multi-omics datasets and visualization using various bioinformatics tools. SysBiolPGWAS provides access to individual post-GWAS tools and a novel custom post-GWAS pipeline which integrates several individual post-GWAS tools and data. The SysBiolPGWAS app was developed to be a one-stop shop for post-GWAS analysis. It targets researchers in the area of the human genome and performs its analysis mainly in the autosomal chromosomes. Availability SysBiolPGWAS web app was developed using JavaScript/TypeScript web frameworks and is available at: https://spgwas.waslitbre.org/. Supplementary information All codes are available in this GitHub repository https://github.com/covenant-university-bioinformatics.