Curso UCIBIO (Module 1 - High-throughput Sequencing Data)

UTC
Description

Online course organized by UCIBIO with the collaboration and support of INCD.

Maximum students: 15 students / per module
Week 1 - OMICS
Week 2 - Modelling

 

The course has 6 independent modules:

     Module 0 - Introduction to HPC (12/September - 27/September)
(required module for the users who don't have any knoledge about HPC)

Online hand-on tutorial on which users will learn how to use the INCD HPC cluster.  

     Module 1 - High-throughput Sequencing Data (12/september)

The development of high-throughput sequencing data has provided complete collections of genomes and transcriptomes, unveiling the complexity of cell biology and the underlying dysregulation of diseases. In this Module, researchers will learn how to obtain and analyze big data using High-Performance Computing. Such knowledge will provide them with the tools to complement their research projects with multi-omics profiles.

     Module 2 - Transcriptome Assembly (13/September)

In this module, we will explore "hands on" the main steps needed to assemble transcriptomes using reference mapping as standard in model organisms from murines to the zebrafish; and, most importantly, assembly when reference mapping is not available. Essential steps, requirements, validation and pitfalls will be addressed.
 

     Module 3 - Phylogenomics (14/September)

Phylogenomics is the application of phylogenetic inference methods to large genomic datasets to infer the evolutionary history of species and their genes. These analyses provide the backbone of evolutionary studies aiming to study the speciation process, population demographics or gene family evolution. This module will provide the basics of phylogenetic inference using maximum-likelihood and Bayesian methods with a hands-on tutorial that takes advantage of HPC resources. 

     Module 4 - Structure-based Virtual Screening (27/September)

Protein-ligand docking is applied to screen virtual databases of millions of compounds predicting ligand's binding properties to specific biomolecular targets of interest. In this module, researchers will learn how to prepare large virtual screening runs using protein-ligand docking tools taking advantage of HPC resources to screening thousands or millions of molecules.

     Module 5 - Molecular Dynamics (28/September)

Molecular Dynamics simulations enable the study of the dynamic properties of biological systems through time with atomistic detail. In this module, researchers will learn how to take advantage of HPC and GPU resources to simulate the interaction between a potential drug-like molecule and an enzyme of pharmacological interest at the nanosecond to microsecond time scale.

     Module 6 - Hybrid Quantum Mechanics/Molecular Mechanics (29/September)

QM/MM methods allow the study of chemical reactions in large systems with great accuracy. This hybrid approach allows the study of the catalytic site with quantum mechanics, while the rest of the system is treated with classical molecular mechanics. This module will introduce the basics of QM/MM simulations in the study of biomolecules using HPC resources.

The registration must be made separately for each module, please use the links above to register.

    • Módulo 0: Introduction to HPC (INCD)
      Conveners: João Paulo Martins Conceição, João Pina (LIP)
      • 1
        Introduction to INCD cluster
        Speaker: Pina João (LIP)
      • 2
        Submiting simple jobs

        With this module, users will learn how to submit basics jobs to the INCD cluster and in the end, they will be able to select CPU or GPU job types.

        Speaker: Pina João (LIP)
      • 3
        Submiting MPI jobs

        The last part of the course will teach the users how to submit MPI jobs and other fine tunning jobs options

        Speaker: Pina João (LIP)
      • 4
        Q&A

        Small discussion slot for question not covered during the course

        Speaker: Pina João (LIP)
    • Módulo 1 - High-throughput Sequencing Data: OMICS

      Software: FastQC, Bowtie and STAR (em imagens Docker)

      1. Presentation
        a. Introduction to High-throughput sequencing data
        b. Data Repositories
        c. Methods for Alignment to genome and transcriptome
      2. Hands-On
        a. Download High Throughput sequencing data
        b. Assess Quality with FastQC
        c. Alignment to genome with Bowtie
        d. Alignment to transcriptome with STAR
      3. Conclusions:
        a. What could be done downstream?
      Convener: Ana Rita Grosso (fct.unl.pt)