The emergence of next-generation sequencing (NGS) has marked a before and after in the advancement of scientific research in Biology and Health Sciences, as well as in some diagnostic processes and clinical screening . More recently, single cell sequencing technologies, which represent an application of NGS techniques, have made it possible to study biological processes with an unprecedented level of detail. Through these techniques, it is possible to obtain a large amount of information related to various cellular processes, typically gene transcription and expression, which are considered "big data".
In order to acquire a biological meaning, this type of data requires an intense process of filtering, analysis and interpretation; which has given way to the creation of a new branch of science called bioinformatics. Bioinformatics is an interdisciplinary science that combines different mathematical, statistical, and computational methods for the analysis of complex biological data. In other words, bioinformatics is the meeting point of programming and mathematics with biology to give biological meaning to data from experiments, and thus test theories and hypotheses.
Today, bioinformatics has become an essential tool for the processing and analysis of data from NGS, both in the research context and in the applied clinical context. These analyzes are usually guided and interpreted by expert personnel in the biological sciences of study, thus allowing important scientific advances in these areas.
In recent years, this branch of science has advanced by leaps and bounds, where various methods that were previously specific to computational systems have been adapted and/or implemented to analyze large amounts of biological data with a wide variety of objectives. However, bioinformatics is not an easy science to learn, and if it is not implemented correctly, it can lead to erroneous conclusions affecting the final results of the experiment. In addition, the large number of tools available (there are currently more than 1,000 public bioinformatics tools (TODO: cites lazzapi website) codified on various computational platforms) and the complexity and specificity of the analyzes make it difficult or even impossible to implement this type of analysis. in research laboratories.