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What evolutionary bioinformatics? 


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Evolutionary bioinformatics is a field that utilizes computational tools and techniques to study the evolution of biological molecules, such as proteins, and their role in cellular and evolutionary processes. It involves the analysis and characterization of genomic, transcriptomic, proteomic, and metabolomic data to understand the regulation of gene expression, protein structure and function, as well as evolutionary processes that lead to structural and functional changes over time . Bioinformatics pipelines and tools are available to track viral sequence diversity and study the origin and evolutionary features of viruses, including the SARS-CoV-2 virus responsible for the COVID-19 pandemic . Evolutionary bioinformatics also aims to provide researchers with up-to-date and high-quality scholarly articles on specific contemporary topics in the field of evolutionary genomics . Additionally, it plays a crucial role in conservation genomics, helping to investigate adaptive evolution, gene family expansions, and genetic load within populations, with the aim of protecting endangered species and preventing mass extinction .

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Evolutionary bioinformatics is the use of bioinformatics tools and techniques to study the evolutionary processes and changes in proteins over time.
Open accessJournal ArticleDOI
Yuval Itan, Gur Pines, Pascale Gerbault 
1 Citations
Evolutionary bioinformatics aims to provide researchers in the field of evolutionary genomics with access to relevant scholarly articles by leading international researchers.
Evolutionary bioinformatics is the use of bioinformatics tools and techniques to study the origin and evolutionary features of viruses, as discussed in the provided paper.
Evolutionary bioinformatics is a tool used to understand the evolution of membrane proteins, such as transient receptor potential channels, by analyzing genetic and sequence data.

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What is the best computational language for bioinformatics?5 answersPython is considered one of the best computational languages for bioinformatics due to its fast learning curve, easy integration in data analysis pipelines, and flexibility in handling and modeling data. Python has gained popularity in the field of bioinformatics and chemoinformatics because of its suitability for handling complex data such as genomics data, medical imaging, and electronic medical records. It allows researchers to adopt powerful bioinformatics methods without requiring extensive technical and programming experience. Additionally, Python provides a wide range of libraries and tools specifically designed for bioinformatics tasks, making it a versatile language for computational biologists.
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