An algorithm and application to efficiently analyze DNA fiber data

The duplication of genetic information (DNA replication) is central to life. Numerous control mechanisms ensure the exact course of the process during each cell division. Disturbances of DNA replication have severe consequences for the affected cell, and current models link them to cancer development. One of the most accurate methods for studying DNA replication is labeling newly synthesized DNA molecules with halogenated nucleotides, followed by immunofluorescence and microscopy detection, known as DNA fiber labeling. The method allows the registration of the activity of single replication complexes by measuring the length of the "trace" left by each of them. The major difficulty of the method is the labor-intensive analysis, which requires measuring the lengths of a large number of labeled fragments. Recently, the interest in this kind of image analysis has grown rapidly. In this manuscript, we provide a detailed description of an algorithm and a lightweight Java application to automatically analyze single DNA molecule images we call "DNA size finder". DNA size finder significantly simplified the analysis of the experimental data while increasing reliability by the standardized measurement of a greater number of DNA molecules. It is freely available and does not require any paid platforms or services to be used. We hope that the application will facilitate both the study of DNA replication control and the effects of various compounds used in human activity on the process of DNA replication.

From Text-based Genome, Population Variations, and Transcriptome Datafiles to SQLite Database and Web Application: A Bioinformatical Study on Alfalfa

In this study, a web database application with the Flask framework was developed to implement three types of queries and visualize the results over a bioinformatical dataset from Alfalfa (Medicago sativa). A backend SQLite database was constructed from genome FASTA, population variations, transcriptome, and annotation files with extensions ".fasta", ".gff", "vcf", ".annotate", etc. Further, a supplementary command-line-based Java application was also developed for faster access to the database without direct SQL programming. Overall, Python, Java, and HTML were the main programming languages used in this application. Those scripts and the development procedures are valuable for bioinformaticians to build online databases from similar raw datasets of other species.

Solução eficiente para balanceamento de carga em servidores de aplicação java / Efficient load balancing solution for java application servers

Atualmente, o desenvolvimento de aplicações para internet é a melhor forma de oferecer facilidade de acesso aos usuários a partir de um computador ou de um dispositivo móvel, pois não é necessário instalar nenhum software adicional. Dentre as diversas soluções para o desenvolvimento de aplicações, a plataforma Java tem se tornado a procurada por ser independente de ambiente computacional, oferecendo uma variedade de bibliotecas, e projetada para executar código com segurança. Assim, aplicações baseadas em Java passaram a automatizar atividades operacionais das áreas administrativa e acadêmica das universidades federais. Em certas ocasiões, estas aplicações podem sofrer uma grande demanda de requisições simultâneas provocando baixos tempos de resposta ou até a interrupção dos serviços. Uma solução para atender a grande demanda de requisições simultâneas é utilizar várias máquinas na rede atuando como um único servidor, através de um balanceamento de carga. Este trabalho apresenta um estudo comparativo entre os balanceadores de carga Apache Server com Tomcat Connector mod_jk e o HAProxy dos servidores de aplicação Java que hospedam os Sistemas Institucionais Integrados de Gestão (SIG/UFRN) da Universidade Federal de Itajubá.

PHENSIM: Phenotype Simulator

Despite the unprecedented growth in our understanding of cell biology, it still remains challenging to connect it to experimental data obtained with cells and tissues’ physiopathological status under precise circumstances. This knowledge gap often results in difficulties in designing validation experiments, which are usually labor-intensive, expensive to perform, and hard to interpret. Here we propose PHENSIM, a computational tool using a systems biology approach to simulate how cell phenotypes are affected by the activation/inhibition of one or multiple biomolecules, and it does so by exploiting signaling pathways. Our tool’s applications include predicting the outcome of drug administration, knockdown experiments, gene transduction, and exposure to exosomal cargo. Importantly, PHENSIM enables the user to make inferences on well-defined cell lines and includes pathway maps from three different model organisms. To assess our approach’s reliability, we built a benchmark from transcriptomics data gathered from NCBI GEO and performed four case studies on known biological experiments. Our results show high prediction accuracy, thus highlighting the capabilities of this methodology. PHENSIM standalone Java application is available at https://github.com/alaimos/phensim, along with all data and source codes for benchmarking. A web-based user interface is accessible at https://phensim.tech/.

Competitive Routing on a variant of Delaunay Triangulation

The concept of Delaunay triangulation is thought to be currently one of the best implementations in the sampling arena, whether it be technical or a non technical domain. Considering the network congestions which cause a competitive routing in any given area of the network, Delaunay triangulation has come to be proven as a good, if not the best, remedy to solve the mentioned problem. Dr. Prosenjit Bose presented a good argument back in November 2011 where he proved that connecting the nodes of any given network using the concepts of Delaunay Triangulation gave the best path between nodes, taking the least amount of time for the communication and reducing the competitive routing in the network by reducing the spanning ratio and path length by almost 5/sqrt(3). Here in this study we use the concepts of the Delaunay Triangulation to design a Java application which analyses given a set of random nodes in a plane, it connects each of them with the use of Delaunay Triangulation so that the nodes have the best path to communicate with each other.

Competitive Routing on a variant of Delaunay Triangulation

The concept of Delaunay triangulation is thought to be currently one of the best implementations in the sampling arena, whether it be technical or a non technical domain. Considering the network congestions which cause a competitive routing in any given area of the network, Delaunay triangulation has come to be proven as a good, if not the best, remedy to solve the mentioned problem. Dr. Prosenjit Bose presented a good argument back in November 2011 where he proved that connecting the nodes of any given network using the concepts of Delaunay Triangulation gave the best path between nodes, taking the least amount of time for the communication and reducing the competitive routing in the network by reducing the spanning ratio and path length by almost 5/sqrt(3). Here in this study we use the concepts of the Delaunay Triangulation to design a Java application which analyses given a set of random nodes in a plane, it connects each of them with the use of Delaunay Triangulation so that the nodes have the best path to communicate with each other.