Dataset for the practice in the data preprocessing and unsupervised learning in the introduction to bioinformatics course

“Bioinformatics: Introduction and Methods,” a Bilingual Massive Open Online Course (MOOC) as a New Example for Global Bioinformatics Education

Modules showing how the NCBI database classifies and organizes information on DNA sequences, evolutionary relationships, and scientific publications. And a module working to identify a nucleotide sequence from an insect endosymbiont by using BLAST

File used for the Introduction to bioinformatics (IBT) Linux practical session course.

In Brazil, training capable bioinformaticians is done, mostly, in graduate programs, sometimes with experiences during the undergraduate period. However, this formation tends to be inefficient in attracting students to the area and mainly in attracting professionals to support research projects in research groups. To solve these issues, participation in short courses is important for training students and professionals in the usage of tools for specific areas that use bioinformatics, as well as in ways to develop solutions tailored to the local needs of academic institutions or research groups. In this aim, the project “Bioinformática na Estrada” (Bioinformatics on the Road) proposed improving bioinformaticians’ skills in undergraduate and graduate courses, primarily in the countryside of the State of Pará, in the Amazon region of Brazil. The project scope is practical courses focused on the areas of interest of the place where the courses are occurring to train and encourage students and researchers to work in this field, reducing the existing gap due to the lack of qualified bioinformatics professionals. Theoretical and practical workshops took place, such as Introduction to Bioinformatics, Computer Science Basics, Applications of Computational Intelligence applied to Bioinformatics and Biotechnology, Computational Tools for Bioinformatics, Soil Genomics and Research Perspectives and Horizons in the Amazon Region. In the end, 444 undergraduate and graduate students from higher education institutions in the state of Pará and other Brazilian states attended the events of the Bioinformatics on the Road project.

This is an introduction to bioinformatics using hemoglobin as an example. The worksheets introduce students to resources to explore the DNA, RNA and polypeptide linear structure with a brief introduction to the quaternary structure of hemoglobin.

Introductory slides for the UCSC Genome Browser. Part of a set of materials available for training on the UCSC tools. Also available is a recording of the same material as a video. Exercises to practice additional skills can also be used for the training. The full training suite is available: http://openhelix.com/ucsc and there is an additional set of materials with more advanced topics: http://www.openhelix.com/ucscadv . BTW: there is a full script in the "notes" area of the slides, but that is not visible in the viewer.

Computational_Genomics_ Instructor: Name: Dr. Rodolfo Aramayo, PhD Email address: raramayo@tamu.edu Location: Department of Biology Room 412A, Biological Sciences Building West (BSBW) Texas A&M University College Station, TX 77843-3258 Description: This repository contains materials used to teach Computational Genomics in the Spring 2023. This course was heavily based on materials extracted from and/or adapted from: ENSEMBL, and ENSEMBL Tutorials and Examples. Genomes. 2nd edition Current Topics in Genome Analysis Galaxy Training Materials Course Topics: History of Bioinformatics History of Genomics Cloning Basics The Carbon Clarke Formula Introduction to Galaxy Genome Files: FASTA Format Uploading Data into Galaxy Introduction to Text Manipulations Introduction to Regular Expressions Introduction to Gene Models and Tables: GFF3 Files Introduction to Genome Annotation Cyverse User Portal Introduction to Genome Browsers (ENSEMBL) Introduction to Comparative Genomics Working with Genome Files Introduction to Sequence Analysis Computational Arithmetics Author: Rodolfo Aramayo (raramayo@tamu.edu) License: All content produced in this site is licensed by: CC BY-NC-SA 4.0

Familiarity with genome-scale data and the bioinformatic skills to analyze it have become essential for understanding and advancing modern biology and human health, yet many undergraduate biology majors are never exposed to hands-on bioinformatics. This paper presents a module that introduces students to applied bioinformatic analysis within the context of a research-based microbiology lab course. One of the most commonly used genomic analyses in biology is resequencing: determining the sequence of DNA bases in a derived strain of some organism, and comparing it to the known ancestral genome of that organism to better understand the phenotypic differences between them. Many existing CUREs — Course Based Undergraduate Research Experiences — evolve or select new strains of bacteria and compare them phenotypically to ancestral strains. This paper covers standardized strategies and procedures, accessible to undergraduates, for preparing and analyzing microbial whole-genome resequencing data to examine the genotypic differences between such strains. Wet-lab protocols and computational tutorials are provided, along with additional guidelines for educators, providing instructors without a next-generation sequencing or bioinformatics background the necessary information to incorporate whole-genome sequencing and command-line analysis into their class. This module introduces novice students to running software at the command-line, giving them exposure and familiarity with the types of tools that make up the vast majority of open-source scientific software used in contemporary biology. Completion of the module improves student attitudes toward computing, which may make them more likely to pursue further bioinformatics study.

Bioinformatics Services Market size was valued at USD 11.1 Billion in 2023 and is projected to reach USD 3.58 Billion by 2031, growing at a CAGR of 15.06% from 2024-2031.

Bioinformatics Services Market: Definition/ Overview

Bioinformatics services cover a wide range of computational tools and methods for managing, analyzing, and interpreting biological data. These services enable the integration of data from domains such as genomics, proteomics, transcriptomics, and metabolomics to provide insights into biological systems. Drug discovery, customized medicine, gene sequencing, and biological data management are some of the most important applications of bioinformatics. Researchers and healthcare professionals use these services to analyze big datasets, detect disease markers, and develop tailored medicines, considerably improving the precision and efficiency of life science research.

Global Bioinformatics market is estimated at US$15.1 billion in 2024 and anticipated to record a CAGR of 13.8% from 2024 to 2030 to reach US$32.8 billion in 2030. The bioinformatics market is driven by advancements in next-generation sequencing (NGS), artificial intelligence (AI), and big data analytics, enhancing data processing capabilities and storage.

Contemporary biology is moving towards heavy reliance on computational methods to manage, find patterns, and derive meaning from large-scale data, such as genomic sequences. Biology teachers are increasingly compelled to prepare students with skills to meet these challenges. However, introducing biology students to more abstract concepts associated with computational thinking remains a major challenge. Analogies have long been used in science classrooms to help students comprehend complex concepts by relating them to familiar processes. Here I present a multi-step procedure for introducing students to large-scale data analysis (bioinformatics workflows) by asking them to describe a common daily task: making toast. First, students describe the main steps associated with this procedure. Next, students are presented with alternative scenarios for materials and equipment and are asked to extend the analogy to accommodate them. Finally, students are led through examples of how the analogy breaks down, or fails to accurately represent, a bioinformatics analysis. This structured approach to student exploration of analogies related to computational biology capitalizes on diverse student experiences to both clarify concepts and ameliorate possible misconceptions. Similar methods can be used to introduce many abstract concepts in both biology and computer science.

In order to introduce students to the concept of molecular diversity, we developed a short, engaging online lesson using basic bioinformatics techniques. Students were introduced to basic bioinformatics while learning about local on-campus species diversity by 1) identifying species based on a given sequence (performing Basic Local Alignment Search Tool [BLAST] analysis) and 2) researching and documenting the natural history of each species identified in a concise write-up. To assess the student’s perception of this lesson, we surveyed students using a Likert scale and asking them to elaborate in written reflection on this activity. When combined, student responses indicated that 94% of students agreed this lesson helped them understand DNA barcoding and how it is used to identify species. The majority of students, 89.5%, reported they enjoyed the lesson and mainly provided positive feedback, including “It really opened my eyes to different species on campus by looking at DNA sequences”, “I loved searching information and discovering all this new information from a DNA sequence”, and finally, “the database was fun to navigate and identifying species felt like a cool puzzle.” Our results indicate this lesson both engaged and informed students on the use of DNA barcoding as a tool to identify local species biodiversity.

Primary Image: DNA Barcoded Specimens. Crane fly, dragonfly, ant, and spider identified using DNA barcoding.

The table provides a short description of the major components of the model employed by each course, highlighting any differences between the two (deviations are indicated by an asterisk (*)).

Introduction

Global AI In Bioinformatics Market size is expected to be worth around US$ 136.3 Million by 2033, from US$ 3.8 Million in 2023, growing at a CAGR of 42.9% during the forecast period from 2024 to 2033. In 2023, North America led the market, achieving over 46.5% share with a revenue of US$ 1.7 Million.

This growth is driven by increasing demand for bioinformatics, decreasing sequencing costs, and significant funding from both public and private sectors for bioinformatics research. Technological advancements and strategic collaborations among leading players, such as Thermo Fisher Scientific, Illumina Inc., and Qiagen, are further fueling market expansion. These collaborations often focus on developing or upgrading bioinformatics tools to efficiently manage biological data essential for gene therapy, drug discovery, and personalized medicine.

Recent developments highlight the market's dynamic growth, with investments accelerating genomic and proteomic data analysis. These advancements are critical for understanding disease mechanisms and identifying therapeutic strategies. AI-powered bioinformatics is revolutionizing the field by enhancing data analysis speed, facilitating discoveries of new disease pathways, and identifying potential therapeutic targets.

Despite its promising growth, the market faces challenges such as the lack of standardized data formats, the need for user-friendly tools, and the complexities of managing large biological datasets. However, with ongoing technological innovations and increased investments, these challenges are expected to be addressed, creating a robust environment for further market expansion.

The 4th German Crop BioGreenformatics Network (GCBN, https://www.denbi.de/gcbn) user training provided a hands-on introduction to useful bioinformatics tools for biologists with little or no previous knowledge. The training enabled biologists to process their own small and large datasets using R and Linux based methods and is entirely computer-based with interspersed lectures. The first part started with an introduction into the use and basic administration (software installation) of the Linux distribution Ubuntu and demonstrated the first steps into the use the R software (trainer Andrea Bräutigam, folder AB). In part two the use of Blast+ in the command line version, of simple Linux commands like 'cut', of Perl scripts and the graphical user interface of the phylogeny tool 'seaview' were demonstrated (trainer Uwe Scholz, folder US). The third session introduced basic concepts and practical tools for processing biological datasets in Linux. In particular, 'awk' and 'sed' were used. Moreover, 'SAMtools' and 'BEDTools' were applied (trainer Martin Mascher, folder MM). In the fourth part 'Introduction to Databases' a quick start guide to use relational databases was presented. By providing easy examples, this lesson set the fundamentals to motivate to use relational database systems as daily bioinformatics tool to store, retrieve and even analyze -omics data in the big data age (trainer Matthias Lange, folder ML). The last part introduced basic statistics to biologist, teach some commonly used statistical methods and demonstrated the creation of graphical visualizations with software R (trainer Yusheng Zhao, folder YZ).

supplemental data file 1 - bryophyte transcriptomes

Data and conda software environment file for the chapter 'Introduction to Python and Pandas' of the SPAAM Community's textbook: Introduction to Ancient Metagenomics (https://www.spaam-community.org/intro-to-ancient-metagenomics-book).

Presentation on teaching introductory bioinformatics with Jupyter notebook-based active learning at the 2019 Great Lakes Bioinformatics Conference

Bioinformatics Services Market will grow from USD 4,399.58 Million to USD 16,297.10 Million by 2034, showing an impressive CAGR of 15.7%.