remove unnecessary #introduction section

topics/admin/tutorials/database-schema/tutorial.md

@@ -20,11 +20,6 @@ contributors:
   - bgruening
 ---
 
-Galaxy Database Schema
-======================
-
-
-# Requirements
 
 For the hands-on examples you need access to a Galaxy server and access to its PostgreSQL database. You can set-up this yourself, or use the Galaxy Docker Image provided by Björn Grüning (https://github.com/bgruening/docker-galaxy-stable). During this tutorial, we will work with the Galaxy Docker Image.
 

topics/assembly/tutorials/ERGA-post-assembly-QC/tutorial.md

@@ -20,8 +20,6 @@ contributors:
 ---
 
 
-# Introduction
-
 The European Reference Genome Atlas (ERGA) is a large-scale project aimed at generating and integrating high-quality reference genomes for a wide range of European organisms. The project will use state-of-the-art sequencing technologies and advanced bioinformatics tools to produce high-quality genome assemblies.
 
 Reference genomes provide a baseline for understanding genetic diversity within and among populations, and can be used to identify populations at risk of genetic erosion. This information is crucial for developing effective conservation strategies and management plans for threatened and endangered species ({% cite Shafer2015 %}). Additionally, by better understanding the genetic basis of important traits, such as disease resistance and adaptation to changing environments, researchers can develop targeted interventions to mitigate the effects of environmental change and prevent the loss of genetic diversity ({% cite Frankham2011 %}). The ERGA project has the potential to greatly benefit biodiversity conservation efforts and advance our understanding of the genetic basis of biodiversity.

topics/assembly/tutorials/assembly-quality-control/tutorial.md

@@ -30,7 +30,6 @@ follow_up_training:
 
 ---
 
-# Introduction
 
 
 In this tutorial, we will assess the assembly quality of 2 assemblies generated with Hifiasm and Flye using PacBio HiFi reads of a species of fungi, *Saccharomyces cerevisiae* INSC1019 and compare the results with the actual reference genome [*Saccharomyces cerevisiae* S288C](https://www.ncbi.nlm.nih.gov/genome/?term=Saccharomyces%20cerevisiae).

topics/assembly/tutorials/assembly-with-preprocessing/tutorial.md

@@ -40,7 +40,6 @@ contributors:
 
 ---
 
-# Introduction
 
 
 In some research or clinical contexts it is not possible, or very hard, to

topics/assembly/tutorials/flye-assembly/tutorial.md

@@ -34,8 +34,6 @@ follow_up_training:
 ---
 
 
-# Introduction
-
 
 In this tutorial, we will assemble a genome of a species of fungi in the family Mucoraceae, *Mucor mucedo*, from PacBio sequencing data. These data were obtained from NCBI ([SRR8534473](https://www.ncbi.nlm.nih.gov/sra/?term=SRR8534473), [SRR8534474](https://www.ncbi.nlm.nih.gov/sra/?term=SRR8534474) and [SRR8534475](https://www.ncbi.nlm.nih.gov/sra/?term=SRR8534475)). The quality of the assembly obtained will be analyzed, in particular by comparing it to a reference assembly, obtained with Falcon assembler, and available on the [JGI website](https://mycocosm.jgi.doe.gov/Mucmuc1/Mucmuc1.info.html).
 

topics/assembly/tutorials/largegenome/tutorial.md

@@ -23,8 +23,6 @@ contributors:
   - annasyme
 ---
 
-# Introduction
-
 *Note: We recommend running this tutorial on either the Galaxy Europe or Galaxy Australia servers. Other servers (such as Galaxy main) have not yet been configured fully for all the tools in this analysis.*
 
 ## What is genome assembly?

topics/assembly/tutorials/mrsa-illumina/tutorial.md

@@ -50,8 +50,6 @@ follow_up_training:
 ---
 
 
-# Introduction
-
 
 In this training you're going to make an assembly of data produced by
 "Complete Genome Sequences of Eight Methicillin-Resistant

topics/assembly/tutorials/mrsa-nanopore/tutorial.md

@@ -52,8 +52,6 @@ abbreviations:
 ---
 
 
-# Introduction
-
 
 In this training you're going to make an assembly of data produced by
 "Complete Genome Sequences of Eight Methicillin-Resistant

topics/assembly/tutorials/vgp_genome_assembly/tutorial.md

@@ -42,7 +42,6 @@ abbreviations:
   QV: consensus accuracy quality value
 ---
 
-# Introduction
 
 Advances in sequencing technologies over the last few decades have revolutionized the field of genomics, allowing for a reduction in both the time and resources required to *de novo* genome assembly. Until recently, second-generation sequencing technologies (also known as {NGS}) produced highly accurate but short (up to 800bp) reads. Those read extension was not long enough to cope with the difficulties associated with repetitive regions. Today, so-called {TGS} technologies, usually known as {SMRT} sequencing, have become dominant in *de novo* assembly of large genomes. TGS can use native DNA without amplification, reducing sequencing error and bias ({% cite Hon2020 %}, {% cite Giani2020 %}). Very recently, Pacific Biosciences introduced {HiFi} sequencing, which produces reads 10-25 kbp in length with a minimum accuracy of 99% (Q20). In this tutorial you will use HiFi reads in combination with data from additional sequencing technologies to generate a high-quality genome assembly.
 

topics/assembly/tutorials/vgp_workflow_training/tutorial.md

@@ -38,8 +38,6 @@ abbreviations:
 ---
 
 
-# Introduction
-
 
 The {VGP}, a project of the {G10K} Consortium, aims to generate high-quality, near error-free, gap-free, chromosome-level, haplotype-phased, annotated reference genome assemblies for every vertebrate species ({% cite Rhie2021 %}). The VGP has developed a fully automated *de-novo* genome assembly pipeline, which uses a combination of three different technologies: Pacbio {HiFi}, Bionano optical maps, and {Hi-C} data.
 

topics/climate/tutorials/climate-101/tutorial.md

@@ -20,18 +20,15 @@ contributors:
 ---
 
 
-# Introduction
-
+The practical aims at familiarzing you with Climate Science and the terminology used by climate scientists. The target audience is not a climate scientist but
+anyone interested in learning about climate.
 
 > <comment-title></comment-title>
 >
 > This tutorial is significantly based on [Getting your hands-on Climate data](https://nordicesmhub.github.io/climate-data-tutorial/).
 >
 {: .comment}
 
-The practical aims at familiarzing you with Climate Science and the terminology used by climate scientists. The target audience is not a climate scientist but
-anyone interested in learning about climate.
-
 > <agenda-title></agenda-title>
 >
 > In this tutorial, we will cover:

topics/climate/tutorials/fates-jupyterlab/tutorial.md

@@ -51,7 +51,6 @@ contributors:
 ---
 
 
-# Introduction
 
 The practical aims at familiarizing you with running CLM-FATES within Galaxy Climate JupyterLab.
 

topics/climate/tutorials/fates/tutorial.md

@@ -42,9 +42,6 @@ contributors:
 ---
 
 
-# Introduction
-
-
 Terrestrial ecosystem models have been widely used to study the impact of climate changes on vegetation and terrestrial biogeochemical cycles in climate modelling community. They are also more and more applied in ecological studies to help ecologists to better understand the processes. But the technical challenges are still too high for most of the ecologists to use them. This practical aims at familiarizing you (especially ecologists) with running a terrestrial ecosystem model (i.e., CLM-FATES) at site-level in Galaxy and analyzing the model results.
 It will also teach you on how to create Galaxy workflow for your site-level CLM-FATES simulations to make your research fully reproducible. We hope this tutorial will promote the use of CLM-FATES and other terrestrial ecosystem models by a broader community.
 

topics/climate/tutorials/pangeo-notebook/tutorial.md

@@ -65,9 +65,6 @@ notebook:
 ---
 
 
-# Introduction
-
-
 In this tutorial, we will learn about [Xarray](https://xarray.pydata.org/), one of the most used Python library from the [Pangeo](https://pangeo.io/) ecosystem.
 
 We will be using data from [Copernicus Atmosphere Monitoring Service](https://ads.atmosphere.copernicus.eu/)

topics/climate/tutorials/pangeo/tutorial.md

@@ -31,11 +31,6 @@ contributors:
 ---
 
 
-# Introduction
-
-
-<!-- This is a comment. -->
-
 [Pangeo](https://pangeo.io/) is a project that effectively began in 2016 with a workshop at Columbia University. The mission for Pangeo developed at that workshop is still valid nowadays:
 
 *Our mission is to cultivate an ecosystem in which the next generation of open-source analysis tools for ocean, atmosphere and climate science can be developed, distributed, and sustained. These tools must be scalable in order to meet the current and future challenges of big data, and these solutions should leverage the existing expertise outside of the geoscience community.*

topics/climate/tutorials/panoply/tutorial.md

@@ -24,17 +24,14 @@ contributors:
 ---
 
 
-# Introduction
-
+The practical aims at familiarzing you with the [Panoply](https://www.giss.nasa.gov/tools/panoply/) Galaxy interactive environment. Panoply is among the most popular tool to visualize geo-referenced data stored in [Network Common Data Form](https://en.wikipedia.org/wiki/NetCDF) (netCDF). It provides a graphical interface for inspecting (show metadata) and visualizing netCDF data. It supports many features to customize your plots and we will introduce some of them in this lesson.
 
 > <comment-title></comment-title>
 >
 > This tutorial is significantly based on [the Panoply documentation](https://www.giss.nasa.gov/tools/panoply/help/) ["Quick View Data with Panoply"](https://disc.gsfc.nasa.gov/information/howto?title=Quick%20View%20Data%20with%20Panoply) section.
 >
 {: .comment}
 
-The practical aims at familiarzing you with the [Panoply](https://www.giss.nasa.gov/tools/panoply/) Galaxy interactive environment. Panoply is among the most popular tool to visualize geo-referenced data stored in [Network Common Data Form](https://en.wikipedia.org/wiki/NetCDF) (netCDF). It provides a graphical interface for inspecting (show metadata) and visualizing netCDF data. It supports many features to customize your plots and we will introduce some of them in this lesson.
-
 In this tutorial, you will learn to:
 - Plot geo-referenced latitude-longitude, latitude-vertical, longitude-vertical, time-latitude or time-vertical arrays.
 - Use any of numerous color tables for the scale colorbar

topics/computational-chemistry/tutorials/analysis-md-simulations/tutorial.md

@@ -36,9 +36,6 @@ contributors:
 ---
 
 
-# Introduction
-
-
 Molecular dynamics simulations return highly complex data. The Cartesian positions of each atom of the system (thousands or even millions) are recorded at every time step of the trajectory; this may again be thousands to millions of steps in length. Therefore, some kind of further analysis is needed to extract useful information from the data.
 
 In this tutorial, we illustrate some of the analytical tools able to investigate conformational changes by analysis of a typical short protein simulation, such as for CBH1.

topics/computational-chemistry/tutorials/cheminformatics/tutorial.md

@@ -22,9 +22,6 @@ contributors:
 ---
 
 
-# Introduction
-
-
 Cheminformatics is the use of computational techniques and information about molecules to solve problems in chemistry. This involves a number of steps: retrieving data on chemical compounds, sorting data for properties which are of interest, and extracting new information. This tutorial will provide a brief overview of all of these, centered around protein-ligand docking, a molecular modelling technique. The purpose of protein-ligand docking is to find the optimal binding between a small molecule (ligand) and a protein. It is generally applied to the drug discovery and development process with the aim of finding a potential drug candidate. First, a target protein is identified. This protein is usually linked to a disease and is known to bind small molecules. Second, a 'library' of possible ligands is assembled. Ligands are small molecules that bind to a protein and may interfere with protein function. Each of the compounds in the library is then 'docked' into the protein to find the optimal binding position and energy.
 
 Docking is a form of molecular modelling, but several simplifications are made in comparison to methods such as molecular dynamics. Most significantly, the receptor is generally considered to be rigid, with covalent bond lengths and angles held constant. Charges and protonation states are also not permitted to change. While these approximations reduce accuracy to some extent, they increase computational speed, which is necessary to screen a large compound library in a realistic amount of time.

topics/computational-chemistry/tutorials/covid19-docking/tutorial.md

@@ -30,8 +30,6 @@ contributors:
 
 ---
 
-# Introduction
-
 
 This tutorial provides a companion to the work performed in March 2020 by InformaticsMatters, the Diamond Light Source, and the European Galaxy Team to perform virtual screening on candidate ligands for the SARS-CoV-2 main protease (MPro). This work is described [in our dedicated site](https://covid19.galaxyproject.org/cheminformatics).
 

topics/computational-chemistry/tutorials/htmd-analysis/tutorial.md

@@ -25,10 +25,6 @@ contributors:
 
 ---
 
-
-# Introduction
-
-
 This tutorial provides an introduction to using high-throughput molecular dynamics to study protein-ligand interaction, as applied to the N-terminal domain of Hsp90 (heat shock protein 90).
 
 

topics/computational-chemistry/tutorials/md-simulation-gromacs/tutorial.md

@@ -28,8 +28,6 @@ contributors:
 ---
 
 
-# Introduction
-
 
 Molecular dynamics (MD) is a method to simulate molecular motion by iterative application of Newton's laws of motion. It is often applied to large biomolecules such as proteins or nucleic acids.
 

topics/computational-chemistry/tutorials/md-simulation-namd/tutorial.md

@@ -34,9 +34,7 @@ contributors:
 
 ---
 
-
-# Introduction
-
+In this tutorial we will perform a simulation with the popular [NAMD](http://www.ks.uiuc.edu/Research/namd/) molecular dynamics software. Please note NAMD tools are not currently available on a public Galaxy server due to licensing issues. If you are interested in following this tutorial, you will need to download the [BRIDGE docker container](https://github.com/scientificomputing/BRIDGE) and [download NAMD](https://www.ks.uiuc.edu/Development/Download/download.cgi?PackageName=NAMD) yourself.
 
 
 > <agenda-title></agenda-title>
@@ -49,7 +47,6 @@ contributors:
 {: .agenda}
 
 
-In this tutorial we will perform a simulation with the popular [NAMD](http://www.ks.uiuc.edu/Research/namd/) molecular dynamics software. Please note NAMD tools are not currently available on a public Galaxy server due to licensing issues. If you are interested in following this tutorial, you will need to download the [BRIDGE docker container](https://github.com/scientificomputing/BRIDGE) and [download NAMD](https://www.ks.uiuc.edu/Development/Download/download.cgi?PackageName=NAMD) yourself.
 
 This tutorial is made up of two parts. In the first section, we will look at preparation of a system (solvation, charge neutralisation, energy minimisation) using CHARMM. In the second section, we will perform an equilibration and production simulation, using NAMD. If you already completed the [Setting up molecular systems]({% link topics/computational-chemistry/tutorials/setting-up-molecular-systems/tutorial.md %}) tutorial, which covers the use of the CHARMM graphical user interface (GUI), you have already prepared your system, so go straight to the [second section](#md-simulations-with-namd), using the files you prepared earlier.
 

topics/computational-chemistry/tutorials/setting-up-molecular-systems/tutorial.md

@@ -34,15 +34,12 @@ contributors:
 
 ---
 
+In this tutorial, we'll cover the basics of molecular modelling by setting up a protein in complex with a ligand and uploading the structure to Galaxy. This tutorial will make use of CHARMM-GUI. Please note that the follow-up to this tutorial (located in [Running molecular dynamics simulations using NAMD]({% link topics/computational-chemistry/tutorials/md-simulation-namd/tutorial.md %})) requires access to NAMD Galaxy tools, which can be accessed using the [Docker container](https://github.com/scientificomputing/BRIDGE) but are currently not available on any public Galaxy server.
+
 > <comment-title>Audience</comment-title>
 > This tutorial is intended for those who are new to the computational chemistry tools in Galaxy.
 {: .comment}
 
-# Introduction
-
-
-In this tutorial, we'll cover the basics of molecular modelling by setting up a protein in complex with a ligand and uploading the structure to Galaxy. This tutorial will make use of CHARMM-GUI. Please note that the follow-up to this tutorial (located in [Running molecular dynamics simulations using NAMD]({% link topics/computational-chemistry/tutorials/md-simulation-namd/tutorial.md %})) requires access to NAMD Galaxy tools, which can be accessed using the [Docker container](https://github.com/scientificomputing/BRIDGE) but are currently not available on any public Galaxy server.
-
 > <agenda-title></agenda-title>
 >
 > In this tutorial, we will cover:

topics/computational-chemistry/tutorials/zauberkugel/tutorial.md

@@ -22,9 +22,6 @@ contributors:
 ---
 
 
-# Introduction
-
-
 Historically, the pharmacophore concept was formulated in 1909 by the German physician and Nobel prize laureate Paul Ehrlich ({% cite Ehrlich1909 %}). According to the [International Union of Pure and Applied Chemistry (IUPAC)](https://iupac.org/), a pharmacophore is defined as “an ensemble of steric and electronic features that is necessary to ensure the optimal supramolecular interactions with a specific biological target and to trigger (or block) its biological response” ({% cite Wermuth1998 %}). Starting from the cocrystal structure of a non-covalent protein–ligand complex (e.g. Figure 1), pharmacophore perception involves the extraction of the key molecular features of the bioactive ligand at the protein–ligand contact interface into a single model ({% cite Moumbock2019 %}). These pharmacophoric features mainly include: H-bond acceptor (HACC or A), H-bond donor (HDON or D), lipophilic group (LIPO or H), negative center (NEGC or N), positive center (POSC or P), and aromatic ring (AROM or R) moieties. Moreover, receptor-based excluded spheres (EXCL) can be added in order to mimic spatial constraints of the binding pocket (Figure 2). Once a pharmacophore model has been generated, a query can be performed either in a forward manner, using several ligands to search for novel putative hits of a given target, or in a reverse manner, by screening a single ligand against multiple pharmacophore models in search of putative protein targets ({% cite Steindl2006 %}).
 
 ![PDB ID: 4MVF]({% link topics/computational-chemistry/images/4MVF-STU.png %} "Crystal Structure of *Plasmodium falciparum* calcium-dependent protein kinase 2 (CDPK2) complexed with staurosporine (STU) with PDB ID: [4MVF](https://www.rcsb.org/structure/4mvf). Image generated using Maestro (Schrödinger LLC, NY).")

topics/contributing/tutorials/create-new-topic/tutorial.md

@@ -18,7 +18,6 @@ contributions:
   - hexylena
 ---
 
-# Introduction
 
 Each training material is related to a topic. All training materials (slides, tutorials, ...) related to a topic are found in a dedicated directory (*e.g.* `transcriptomics` directory contains the material related to exome sequencing analysis).
 

topics/contributing/tutorials/create-new-tutorial-content/tutorial.md

@@ -28,7 +28,6 @@ abbreviations:
   JSON: JavaScript Object Notation
 ---
 
-# Introduction
 
 Once we have set up the infrastructure, we are ready to write the tutorial.
 

topics/contributing/tutorials/create-new-tutorial-tours/tutorial.md

@@ -18,7 +18,6 @@ contributors:
   - shiltemann
 ---
 
-# Introduction
 
 
 Galaxy is a great solution to train the bioinformatics concepts:

topics/contributing/tutorials/create-new-tutorial/tutorial.md

@@ -22,7 +22,6 @@ contributors:
   - lldelisle
 ---
 
-# Introduction
 
 
 Galaxy is a great solution to train bioinformatics concepts:

topics/contributing/tutorials/design/tutorial.md

@@ -52,9 +52,6 @@ contributions:
     - gallantries
 ---
 
-# Introduction
-
-
 **Teaching and training**, core elements of academic life, can be enormously
 rewarding but also quite challenging. Instructors are often required to perform
 under various constraints, and frequently have to accommodate, engage and

topics/contributing/tutorials/generating-pdf/tutorial.md

@@ -13,9 +13,6 @@ contributors:
   - bebatut
 ---
 
-# Introduction
-
-
 The website with the training material can be run locally. Sometimes, it is also interesting to freeze the tutorials or to get PDFs of the tutorials.
 
 > <agenda-title></agenda-title>

topics/contributing/tutorials/github-command-line-contribution/tutorial.md

@@ -26,7 +26,6 @@ contributors:
   - bebatut
 ---
 
-# Introduction
 
 
 Most of the content is written in [GitHub Flavored Markdown](https://guides.github.com/features/mastering-markdown/) with some metadata (or variables) found in [YAML](http://yaml.org/) files. Everything is stored on a [GitHub](https://github.com) repository: [{{ site.github_repository }}]({{ site.github_repository }}).

topics/contributing/tutorials/github-interface-contribution/tutorial.md

@@ -18,8 +18,6 @@ contributors:
   - bebatut
 ---
 
-# Introduction
-
 
 All the training material which you find on [{{ site.url }}{{ site.baseurl }}/]({{ site.baseurl }}/) is stored on a [GitHub](https://github.com) repository ([{{ site.github_repository }}]({{ site.github_repository }})), a code hosting platform for version control and collaboration. GitHub interface is quite intuitive and simplifies the contributions from anyone.
 

topics/contributing/tutorials/gitpod/tutorial.md

@@ -16,8 +16,6 @@ contributors:
 ---
 
 
-# Introduction
-
 
 If you are working on your own training materials and want preview them online without installing anything on your computer, you can do this using GitPod!