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Souvik Chakraborty

A complete guide to the development of ideas for in-silico research to the publication of a paper - yes this is what you get

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A complete guide to the development of ideas for in-silico research to the publication of a paper - yes this is what you get

From idea development for research to writing and publishing a paper, yes that is what you get. Learn the basics of data analysis for gene expression analysis, molecular docking, visualization of the docked complex, enrichment analysis, microRNA identification production of publication-quality images, writing a research article properly, and using Zotero - a free reference management tool. In this course, you will be getting a proper idea of how can a set of genes can be used to design drugs and how using molecular docking techniques we can validate our results for the best drug. You will be getting a good idea of 'drug repurposing' also after the completion of the hands-on training session associated with this course. No prior knowledge or skills are required to attain this course and this course is deliberately kept straightforward for new learners.

In this course, you will get all the necessary skills required to write a research article on your own, guidelines for selecting a proper journal for your manuscript, and also you can extend these research ideas to wet-lab experiments as well.

ALL THE BEST:)

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What's inside

Learning objectives

  • Perform gene expression analysis
  • Create a protein-protein interaction map and calculate hub genes using cytoscape
  • Screening of potential drug targets
  • Admet analysis of drugs drulito and osiris
  • Perform molecular docking using autodock vina
  • Visualization of the docked complex using biovia discovery studio
  • Enrichment analysis using enrichr
  • Finding micrornas associated with hub genes using mirnet
  • Manuscript preparation and using a bibliographic management tool (zotero will be used)
  • Select a proper journal (scopus indexed as well as pubmed indexed) for your first paper.
  • Uploading a paper to biorxiv (getting doi for your first paper)
  • Show more
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Syllabus

Introduction
Intro to the course
Study Plan
Data analysis and Manipulation
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Covers molecular docking techniques, which are essential for validating drug design results and understanding drug repurposing, providing practical skills for pharmaceutical research
Teaches gene expression analysis, a fundamental skill for understanding gene function and regulation, which is applicable in various biological research areas
Develops skills in creating protein-protein interaction maps using Cytoscape, a valuable tool for identifying key genes and understanding biological pathways
Includes instruction on using Zotero for reference management, which is crucial for maintaining accurate citations and streamlining the research writing process
Employs DruLiTo and OSIRIS for drug screening, but these tools may have newer alternatives that offer enhanced features or more up-to-date data
Requires Adobe Photoshop for producing publication-quality images, which may pose a barrier to learners who do not have access to this paid software

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Reviews summary

Bioinformatics research: from idea to article pipeline

According to learners, this course offers a largely positive dive into bioinformatics research, providing a practical, step-by-step guide to navigate the entire pipeline, from developing an idea to publishing an article. Students frequently praise the hands-on sessions, particularly highlighting the use of tools like Cytoscape and Autodock Vina as excellent for gaining practical skills. While the course structure covering the full research process is a significant strength, some reviewers note that despite the claim of no prerequisites, having some prior biological knowledge is beneficial. Additionally, concerns were raised by some about certain topics lacking depth and difficulties with troubleshooting software installations, suggesting it might require additional self-study for a complete understanding.
Guides learners from idea to publication.
"This course offers a practical, step-by-step guide to navigate the entire pipeline, from developing an idea to publishing an article."
"Excellent hands-on guide. Demystifies the whole pipeline from idea to publication."
"Delivered exactly what was promised - a guide from idea to article."
Offers valuable practical experience.
"Great overview, loved the practical tools like Cytoscape and Vina. Helped me understand the research process end-to-end."
"Useful for learning the workflow. Docking part was good. I appreciated the practical focus."
"Excellent hands-on guide. Demystifies the whole pipeline from idea to publication. Very practical focus."
"Highly recommended for a practical start in bioinformatics research. The step-by-step approach is fantastic."
Issues with software setup/use noted.
"Struggled with technical setup and the pace was uneven."
"Software setup was tricky."
"Troubleshooting is hard."
May require prior biological background.
"Needs prior biology background for sure, not truly for absolute beginners."
"Not for absolute beginners. Assumes too much prior knowledge."
"Better if you have some background already."
Some areas could be more detailed.
"Introduces many tools, but sometimes rushed. Lacked depth in explanations of concepts."
"Still feels like just the surface on some bio topics."
"Coverage is broad rather than deep. Explanation depth varies."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Basics of Bioinformatics research - from idea to article with these activities:
Review Basic Biology Concepts
Reviewing fundamental biology concepts will provide a solid foundation for understanding gene expression analysis and molecular docking, which are key components of the course.
Show steps
  • Review your notes from introductory biology courses.
  • Complete practice quizzes on basic biological processes.
  • Watch videos explaining the central dogma of molecular biology.
Compile a List of Bioinformatics Resources
Compiling a list of useful bioinformatics resources will help you stay organized and efficient in your research.
Show steps
  • Gather links to useful databases, tools, and websites.
  • Organize the resources by category (e.g., sequence analysis, docking).
  • Add brief descriptions of each resource and its purpose.
Read 'Bioinformatics for Dummies'
Reading this book will provide a broad overview of bioinformatics principles and tools, making the course material easier to grasp.
Show steps
  • Read the introductory chapters covering basic bioinformatics concepts.
  • Focus on chapters related to data analysis and molecular biology.
  • Take notes on key terms and concepts for later review.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Follow Online Tutorials for Cytoscape
Following online tutorials for Cytoscape will help you master the software for creating and analyzing protein-protein interaction networks.
Show steps
  • Search for online tutorials on Cytoscape's website or YouTube.
  • Follow the tutorials to create and customize a PPI network.
  • Explore different layout options and network analysis tools.
Create a Presentation on Molecular Docking
Creating a presentation on molecular docking will reinforce your understanding of the process and its applications in drug discovery.
Show steps
  • Research the principles and methods of molecular docking.
  • Prepare slides explaining the different steps involved in docking.
  • Include examples of successful drug discoveries using docking.
  • Practice your presentation to ensure clarity and conciseness.
Analyze Publicly Available Gene Expression Data
Starting a small project analyzing publicly available gene expression data will provide hands-on experience with the techniques taught in the course.
Show steps
  • Find a publicly available gene expression dataset on GEO or ArrayExpress.
  • Use online tools to perform basic differential expression analysis.
  • Visualize the results using heatmaps or volcano plots.
  • Write a short report summarizing your findings.
Explore 'Essential Bioinformatics'
Reading this book will provide a more in-depth understanding of the theoretical concepts behind the bioinformatics tools and techniques used in the course.
Show steps
  • Read chapters related to sequence alignment and database searching.
  • Study the sections on gene expression analysis and network biology.
  • Work through the examples and exercises provided in the book.

Career center

Learners who complete Basics of Bioinformatics research - from idea to article will develop knowledge and skills that may be useful to these careers:
Drug Discovery Researcher
A Drug Discovery Researcher identifies and develops new drug candidates, and this course is directly suited to build a foundation in this field. This type of researcher will use bioinformatics software to analyze biological data and find potential drug targets, and the course covers this process in detail. The ability to perform molecular docking, ADMET analysis, and drug repurposing, all taught in the course, makes it extremely relevant to the drug discovery process. Also, the course's emphasis on publication provides a path toward communicating findings to the scientific community.
Computational Biologist
A Computational Biologist develops and applies computational and mathematical methods to study biological problems. This career is strongly supported by this course, which teaches essential skills for analyzing complex biological data. In this role, one might use gene expression data to discover new drug targets, develop models to simulate biological processes, or work with large datasets to uncover patterns. The course's hands-on training in molecular docking and microRNA identification is directly applicable to the work of a computational biologist, and skills in generating publication-quality figures will be important to effectively communicate your work.
Bioinformatician
A Bioinformatician combines biology with computer science to analyze biological data and this course is ideal for someone interested in this career. A Bioinformatician develops tools, databases, and workflows to handle large-scale genomic datasets. The course's modules on gene expression analysis, protein-protein interaction network creation, and drug target screening align with the activities of a bioinformatician. This course is especially helpful for those who need to perform molecular docking, identify microRNAs, and produce publication-ready images, all standard tasks for a bioinformatician.
Bioinformatics Scientist
A Bioinformatics Scientist uses computational tools and methods to analyze biological data. This course provides a strong basis for this role by covering key techniques like gene expression analysis, molecular docking, and enrichment analysis, which are crucial for understanding biological systems at a molecular level. A person in this role will often work with genomic data to uncover insights for disease management, drug development, and fundamental biological research. The course's focus on practical skills like creating protein-protein interaction maps, screening drug targets, and generating publication-quality images will greatly help a bioinformatics scientist.
Bioinformatics Analyst
A Bioinformatics Analyst uses computational tools to interpret biological data and this course is a strong foundation for this role. A person in this field uses computational methods to analyze large datasets of genomic, proteomic, and other biological data. The course's focus on gene expression analysis, molecular docking, and enrichment analysis will be extremely helpful to a bioinformatics analyst. The course's emphasis on practical skills such as creating protein-protein interaction maps, screening drug targets, and generating publication-quality images will be directly applicable to tasks in this career. The knowledge of manuscript preparation will be a great asset for communicating findings.
Genomic Data Analyst
A Genomic Data Analyst works with genomic datasets to extract meaningful insights and this course provides critical foundations for this role. This role often involves analyzing gene expression data, identifying differentially expressed genes, and characterizing gene networks, all of which are covered in the course. The course's training in using tools like Cytoscape, Enrichr, and miRNet is directly applicable to the tasks of a genomic data analyst. A person in this role will often use bioinformatic tools to discover and understand the underlying genetics of diseases, develop biomarkers, and contribute to genomic research at large.
Scientific Writer
A Scientific Writer creates written documentation about scientific topics and this is the perfect course to learn how to publish your findings. This role involves preparing research papers, reports, and other forms of scientific communication. This course is directly useful because it provides a blueprint for writing a research paper, selecting a journal, and using reference management tools. Scientific writers may also need to visualize results, and the training in the course on generating publication quality images is directly applicable. The course provides the perspective of the researcher, which may greatly help someone wishing to write scientific publications.
Research Scientist
A Research Scientist conducts experiments and studies to expand scientific knowledge. In a biology-focused role, this course is a great fit, teaching many techniques needed to carry out in-silico research. A researcher might use the course's practical skills in data analysis, molecular docking, and enrichment analysis to investigate biological phenomena. The course's guidance on writing a research article, preparing manuscripts, and selecting a journal will help the researcher communicate their findings effectively with the scientific community. Although this role often requires an advanced degree, this course helps build a solid foundation.
Research Associate
A Research Associate assists with research projects and this course is a great fit for those looking to work on computation biology projects. This course provides training in vital techniques such as gene expression analysis, molecular docking, and enrichment analysis. A research associate may utilize the course to conduct data analysis, screen drug targets, or develop molecular models. Moreover, the focus on preparing manuscripts and using reference management tools will aid the associate in documenting and sharing research outcomes. While this role exists in many fields, the skills in this course will help someone working in biology or biochemistry labs.
Biotechnology Research Associate
A Biotechnology Research Associate assists in conducting research in biotechnology. This course provides valuable hands-on experience in computational biology techniques that may be highly relevant in this role. This position may perform tasks like gene expression analysis, drug target screening, and molecular docking, all of which are covered in the course. The course's focus on producing publication quality images may help in communicating research findings. Learning to use tools such as Cytoscape, Enrichr, and miRNet can be beneficial for a research associate involved in bioinformatics research projects.
Genetics Researcher
A Genetics Researcher studies genes, heredity, and genetic variation, and this course may be helpful for those working with computational methods. The course emphasizes gene expression analysis, protein-protein interaction networks, and microRNA identification, all of which are essential for modern genetics research. A genetics researcher might use this course's focus on bioinformatics tools and techniques to analyze genomic data and develop new understandings of biological systems. The skills in manuscript preparation and the use of a bibliographic management tool, taught in this course, will be useful for communicating findings.
Data Scientist
A Data Scientist analyzes large datasets to derive insights, and this course may be useful for those specializing in biological data. This course teaches many techniques for manipulating and analyzing biological data, which may be essential for data scientists who focus on genomics, proteomics, or other omics data. The course helps build a foundation of skills in performing gene expression analysis, creating protein interaction maps, and conducting enrichment analysis. The data visualization techniques taught in the course, as well as the focus on producing publication quality images, may be useful to communicating findings.
Systems Biologist
A Systems Biologist studies biological systems as a whole rather than focusing on individual components or processes. The content of this course may be useful for those who wish to use computational methods in systems biology. The course's emphasis on integrating data from different sources and creating protein interaction maps is highly relevant to a systems biology researcher. The lessons on gene expression analysis and enrichment analysis can provide a solid foundation for someone in this role. While a Systems Biologist often needs an advanced degree, this course may help build a foundation.
Biochemist
A Biochemist studies chemical processes within living organisms, and this course may be useful for those specializing in computational or in-silico methods. The course includes training in molecular docking, ADMET analysis, and the use of bioinformatics tools relevant to biochemistry. A biochemist may use the course's techniques in drug discovery or to understand how biological systems work at a molecular level. While this course primarily focuses on in-silico research, the skills learned can be used to support bench work or communicate findings. An advanced degree is sometimes required for this role.
Molecular Biologist
A Molecular Biologist studies the structure and function of molecules essential to life, and this course may be useful if you are interested in the computational aspects of this role. The course's exploration of molecular docking, ADMET analysis, and drug target screening will enhance a molecular biologist's ability to understand how biological molecules interact. Additionally, skills in using bioinformatics tools and techniques taught in the course can substantially improve the efficiency of molecular biology work. Although the course focuses on in-silico methods, the knowledge gained may be valuable for wet lab molecular biology work.

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Basics of Bioinformatics research - from idea to article.
Provides a comprehensive overview of bioinformatics, covering a wide range of topics from sequence analysis to systems biology. It is particularly useful for students seeking a deeper understanding of the underlying principles and algorithms used in bioinformatics research. The book can be used as a reference for understanding the theoretical aspects of gene expression analysis, molecular docking, and network analysis. It is often used as a textbook in bioinformatics courses at the undergraduate and graduate levels.
Provides a gentle introduction to the field of bioinformatics, covering essential concepts and tools in an accessible manner. It is particularly helpful for beginners with limited prior knowledge in bioinformatics. The book serves as a useful reference for understanding the basic principles behind data analysis, gene expression, and molecular docking. While not a comprehensive textbook, it offers a solid foundation for further exploration.

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