In this repository I outline a brief description or a general overview of Bioinformatics, that can serve as foundational knowledge before venturing into Bioinformatics. Glad to see you here.:smile: Lets dig in :arrow_heading_down:
- Overview
- Biologiocal Data Used in Bioinformatics
- Reasons to study Bioinformatics
- Key Concepts In Bioinformatics
- License
- Contributing
- Important links
- Contact
Bioinformatics is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data.
The subsequent process of analyzing and interpreting data is referred to as computational biology.
Bioinformatics is fundamental in biological research and involves biologists who learn programming, or computer programmers, mathematicians or database managers who learn the foundations of biology.
Bioinformatics enables handling huge amounts of data involved and make sense of them.
It involves processing, storing and analysing biological data. This might include:
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Creating databases to store experimental data
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Predicting the way that proteins fold up.
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Modelling how all the chemical reactions in a cell interact with each other
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Transcriptomics-: the study of the transcriptome, the full set of RNA transcripts in a cell. Genes aren’t constantly active. They can be turned on and off by proteins and chemical messengers. A gene that is turned on, or expressed will be used to produce RNA which is then used as the assembly instructions for a protein. Scientists can use RNA sequencing to compare gene expression in different cell types, for example between healthy and diseased cells.
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Proteomics: the study of the complete set of proteins in a cell or system. Genes provide the information our cells use to make proteins, which are the machinery of the cell. Scientists can analyse a tissue sample and see what proteins can be found in it.
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Phenomics: the study of phenotypes at a genome-wide scale. A phenotype is the way scientists describe something that can be measured about an organism,the observable features of an organism.An organism's phenotype results from two basic factors: the expression of an organism's genetic code (its genotype) and the influence of environmental factors. Bioinformatics lets us look for possible links between the DNA and a phenotype.
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Chemoinformatics: the computational analysis of chemical and biochemical data. Drug research generates lots of experimental data. Big databases of drug information can help researchers develop new drugs, by providing examples of chemicals that target a certain protein.
Studying bioinformatics can open up a wide range of exciting and rewarding career opportunities in the fields of Research, biology, medicine, and computer science. Here are a few reasons why you might want to consider bioinformatics:
- The ability to analyze complex biological data: With the explosion of biological data generated by genomics, proteomics, and other 'omics' technologies, there is an increasing demand for experts who can develop and apply computational tools to manage and analyze this data. Bioinformaticians are well positioned to address this challenge.
- Opportunities to make a difference in human health: Bioinformatics is essential for advancing our understanding of complex diseases such as cancer, cardiovascular diseases, and neurological disorders. As a bioinformatician, you could contribute to developing new treatments and improving patient outcomes.
- Career versatility: Bioinformatics is a highly interdisciplinary field, and studying it can provide you with a diverse skill set that is extreamly valuable.
- Exciting research opportunities: Bioinformatics is a rapidly evolving field, and there are many exciting research opportunities to explore. From developing new algorithms for analyzing genomic data to studying the microbiome, bioinformatics research can make a significant impact on our understanding of the natural world.
Overall, bioinformatics provides you with a challenging and rewarding career that combines cutting-edge computational and biological techniques to solve complex problems. If you're interested in biology, computer science, and problem-solving, bioinformatics could be the perfect field for you.
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Biological sequence databases - Biological databases include NCBI, PDB, etc.. These databases are important as they contain the sequence and structure of protein or nucleotide sequences whether sequenced or hypothesized. These databases contain different kinds of drugs including natural inhibitors, metabolites, FDA-approved drugs, and much more. They are quite useful in drug designing.
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Structure modeling - Structure modeling is amongst the basic steps involved in studying a particular protein or in the drug designing process. It could be done for a protein, DNA, or RNA. There are several webservers and software available for structure modeling.
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Molecular docking/ Computational docking - This is one of the important techniques of bioinformatics that is utilized in the drug designing process. It helps in analyzing the interactions between a target protein and a ligand in order to select potential drugs. Different kinds of software are available to perform docking based on different algorithms.
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Molecular dynamics (MD) simulation - MD simulation is another important technique in bioinformatics. It could be difficult to understand especially when you are from a different field such as computer science. But it is important to learn. It helps to understand the behavior of a protein, or a complex, or a molecule under simulated environmental conditions. You can check the stability of a docked complex by using this technique. Undoubtedly, you will be using a software for MD simulation.
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Command-line proficiency - It is very important to be comfortable working in a Linux environment. One will have to run a lot of software that is only command-line-based.
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Programming languages - Now, it is a must in the field of bioinformatics to learn some programming language such as Python, R, PHP, etc.These languages are helpful in developing new software or bioinformatics tools that are in demand these days.I have included useful resources on this, here.
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Phylogenetics/ Evolutionary studies - Phylogenetics is important to understand the phylogeny of an organism or a species or a genus. You will have to learn different tools to perform phylogenetics. Evolutionary studies help to understand the evolution of a gene, protein, species, genus, or organism. You may have to use a set of tools to finally trace the evolutionary history.
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Sequence analysis - Similarity/homology search, multiple sequence alignment, phylogenetics etc., all are useful methods for sequence analysis. Sequence analysis is helpful in identifying unknown sequence functions, their structure, and other important properties. You will have to learn different techniques that you can subject your sequence to for its analysis.
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Sequencing methods and data analysis - DNA/RNA sequencing methods are another important concept in bioinformatics. That includes a next-generation sequence (NGS) and its data analysis, RNAseq-data analysis, and so on. Most labs work on NGS data.Becoming an expert in this offers many opportunities in research.
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Database development and management - Biological databases are considered as one of the important resources of information in bioinformatics.It is important learn how the databases are developed and managed on servers. Besides, learning to create websites/webpages, back-end, and front-end processing would be a plus.
Files in this Repository are organised as follows;
| File | Contents |
|---|---|
README.md |
General Info. |
Curriculum Checklist |
List of Bioinformatics Topics |
This project is licensed under the MIT License.
As indicated earlier,Contributions to this repository are welcome;If you have any improvements, suggestions, or additional resources to share, please feel free to create pull requests
Don't forget the cardinal rule when working with someone elses code: "Always leave the code you are editing a little cleaner than you found it"
For further assistance and enquiries ,I can be reached at [email protected]. Cheers ! 👏 All the best in exploring Bioinformatics.