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Next Course: “Unveiling Prokaryotic Traits Through Whole Genome Sequencing Data Analysis”, August 2025

Apply for a scholarship to participate in the course coordinated by Dr. Julian Rafael Dib at Planta Piloto PROIMI-CONICET in Tucumán, Argentina

Next-generation sequencing (NGS) plays a crucial role in developing improved microbial strains for bioproducts. However, effective data analysis requires significant bioinformatics expertise. Large datasets, data management needs, and infrastructure limitations pose significant challenges, hindering the utilization of NGS data. This training addresses these identified gaps by enhancing the bioinformatics capacities of participants and preparing them with essential computational skills for analyzing Illumina and Nanopore sequencing data. The course will cover fundamental aspects such as quality assessment, genome assembly, annotation, and identification of relevant features. During the practical learning sessions, we will combine theory with discussion and hands-on exercises, including comparative genomics, taxonomic assignment, and functional annotation. Participants will be introduced to Linux, the command line, scripting, and bioinformatics software tools.

 

By the end of the training, participants will be equipped with the necessary skills to analyze NGS data and support their ongoing research. They will also be empowered to leverage bioinformatics tools effectively in future biological research endeavors.

 

This course seeks to provide participants with the bioinformatics skills necessary to analyze whole-genome sequencing data from Illumina and Nanopore platforms, fostering their ability to effectively utilize these technologies in prokaryotic research.

 

Topics's summary

 

Linux/ Unix systems: Fundamental concepts of command-line navigation and scripting. Hands-on experience navigating the command-line, mastering essentials for file manipulation, directory navigation, and remote server interactions. File system hierarchy, file properties and ownership concepts. Practical examples relevant to biological data manipulation and analysis. 

Grasp the complete NGS workflow: From sample preparation to sequencing and initial data analysis. Characteristics, advantages, and challenges of Illumina short-read and Nanopore long-read sequencing platforms, impacts in data analysis strategies. Master quality control techniques: tools for assessing and enhancing the quality of NGS data, with a focus on addressing the variability in DNA quality derived from different strains and preparing data for accurate genomic analysis. 

Understand assembly algorithms: foundational knowledge of the De Bruijn graph algorithm and contig overlap methods. Navigate assembly workflows: Learn the step-bystep processes involved in using SPAdes for assembling short-read NGS data and Unicycler for performing hybrid assemblies that leverage both short and long-read data. 

Evaluate assembly outcomes: Develop the ability to critically assess the impact of different assembly methodologies on genome completeness and integrity. 

Bacterial genome annotation: annotation strategy according to the organism of interest and available resources, bioinformatics tools for bacterial genome annotation. 

Comparative genomics: bioinformatics tools for comparative genomics. Bioinformatics for biotechnology: finding features of interest: use of bioinformatics tools for the identification and characterization of potential bioactive compounds encoded within bacterial genomes.

 

Application procedure

Applications will be received via this form

Interested candidates will be required to submit a motivation letter and a short CV. Applicants should have sufficient English proficiency. Affiliation with an academic institution or public research center in the applicant's country of residence is required.

Full and partial scholarships are available, including flight, accommodation and meals.

For more information, send your questions to lab.bio.citrus@gmail.com

Last day to apply: April 30th, 2025.

Dib genomics NGS tucuman biolac

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