طراحی و معرفی نرم‌افزار FAND جهت تسهیل استفاده از اطلاعات ژنوم NCBI در آنالیزهای بیوانفورماتیک

The National Center for Biotechnology Information (NCBI) stands as the largest genome data repository globally, housing genetic information spanning all living organisms, from viruses to complex eukaryotes, including humans and plants, through its extensive database, GenBank. Over the past two to three decades, the volume of genomic data available has dramatically expanded, particularly with the advent of next-generation sequencing (NGS) technologies. In earlier years, comprehensive bioinformatic analyses of viral genomes, such as potyviruses, were feasible due to the limited data available. However, as of today, with over 34,000 entries related to potyviruses alone, exhaustive studies have become increasingly challenging.
To address this issue, we introduce the Facilitate Access to NCBI Data (FAND) software, which streamlines the process of analyzing and interpreting vast datasets from the NCBI. FAND enhances data accessibility by efficiently extracting, organizing, and tabulating genetic information. One of its innovative features is a geolocation tool that visually represents the geographic distributions of viruses and their hosts, thus aiding in epidemiological studies.
Key functionalities of FAND include the ability to perform custom slicing of sequences according to user-defined criteria, enabling precise pre-processing of data. Additionally, the software features rapid sequence alignment capabilities for quick and efficient comparisons of trimmed sequences. To support in-depth genetic analysis, the FAND toolkit also includes a gene similarity evaluation module that utilizes recombination analysis to generate detailed similarity diagrams, illustrating the degree of nucleotide conservation across homologous sequences.
Designed to furnish researchers with an integrated and user-friendly platform for genetic data analysis, FAND combines robust data mining, visualization, and computational biology tools into a single accessible package. This software has already demonstrated its utility in addressing various viral datasets, particularly within the realm of plant virology, facilitating advances in research and epidemiological analysis. This version enhances readability and coherence while emphasizing the significance of the software and its applications in the field of genomic research.