DetectiV

Living cells are complex, dynamic, self-regulatory, interactive systems, showing differential states across time and space. Complexity of cellular systems is highlighted with the multi-layered regulatory mechanisms involving the interactions between bio-molecules (such as DNA, RNA, mi-RNA and proteins). These interactions are analyzed in the form of static networks. Likewise, number of experimental techniques like microarray, RNASeq allows quantification of cellular dynamics and aid in discerning differential gene expression across diverse conditions. Computational biology is in need of methods for integration of static networks and gene expression data, since it provides interesting insights into the dynamics of biological systems. DEN is an R/Bioconductor based package designed to assemble different types of human bio-molecular interactions as a complete interactome and contains functions to extract dynamic active networks by integration of gene expression data.

DEW is a platform that allows users to explore RNA-Seq data. A web-based Graphical User Interface is included. The analysis proceeds as such: gapped alignments are performed and corrected for length, PCR and fragment bias so that a Fragment Per (effective) Kilobase per Million of reads (FPKM) is estimated as well as the simpler Reads Per Kb per Million of reads (RPKM). When provided with multiple isoforms and in the ‘contextual’ mode, corrections include a expectation maximization algorithm estimates effective expression profiles and a corrected alignment is produced. For each gene the user provides, DEW computes coverage descriptive statistics (RPKM, FKMP and total, mean and median corrected counts), expression profiles (normalized as R/FPKM and trimmed mean of fold change). DEW allows users to explore the data by providing interactive graphs.

Program that compares the time of execution between a Neural Network and the formula of distance.

DnaFVP is a cutting-edge bioinformatics project that revolutionizes the way DNA sequences are analyzed and visualized. This project falls under the categories of Free, Bio-Informatics, Programming & Tech, Perl, Technology, and S/R. It is a powerful tool designed for researchers, scientists, and bioinformatics enthusiasts who work with DNA data. The primary purpose of DnaFVP is to provide a user-friendly interface for analyzing DNA sequences, identifying patterns, and visualizing genetic data. It leverages the Perl programming language to process and analyze large volumes of DNA information quickly and efficiently. Scientists and researchers can use DnaFVP to gain insights into genetic structures, identify mutations, and compare DNA sequences across different species. By utilizing DnaFVP, users can streamline their DNA analysis workflows, saving time and resources. The project's efficient algorithms and tools enable researchers to uncover hidden patterns in DNA sequences, leading to breakthrough discoveries in the field of bioinformatics. Statistically, DnaFVP has been downloaded by thousands of users worldwide and has received positive feedback for its performance and versatility. It has become a go-to tool for bioinformatics professionals and students alike, showcasing its importance in the field of DNA analysis and research. For those interested in delving deeper into DNA analysis and bioinformatics, DnaFVP offers a comprehensive platform that simplifies complex genetic data analysis. With its robust features and user-friendly interface, DnaFVP empowers users to unlock the secrets hidden within DNA sequences and advance their research in the ever-evolving field of genetics. If you are a bioinformatics researcher, scientist, or enthusiast looking for a powerful tool to analyze and visualize DNA sequences, DnaFVP is the ideal solution to take your research to the next level.