Introducing Bioinformatics
Bioinformatics in the Big Data Era
How to get into Bioinformatics?
How to learn and practice Bioinformatics?
Bioinformatics Careers and Salaries Worldwide
Applications of Bioinformatics
Take-Home Messages
I spoke on "Big Data in Biology". The talk basically concentrates on how biology has affected big data and how big data has become a key player in biology. I have also covered how DNA storage can address long term archival storage.
I spoke on "Big Data in Biology". The talk basically concentrates on how biology has affected big data and how big data has become a key player in biology. I have also covered how DNA storage can address long term archival storage.
Single Nucleotide Polymorphism (SNP)
Polymorphism is a generic term that means 'many shapes‘. It is the ability to appsear in different form .
A single nucleotide polymorphism (SNP) is a DNA sequence variation occurring when a single nucleotide - A, T, C, or G - in the genome differs between members of a species (or between paired chromosomes in an individual).
For example, two sequenced DNA fragments from different individuals, AAGCCTA to AAGCTTA, contain a difference in a single nucleotide. For a variation to be considered a SNP, it must occur in at least 1% of the population.
CHARACTERISTICS OF SNP
• In human beings, 99.9 percent bases are same.
• Remaining 0.1 percent makes a person unique.
• Different attributes / characteristics / traits
• How a person looks, diseases he or she develops.
These variations can be:
Harmless (change in phenotype)
Harmful (diabetes, cancer, heart disease, Huntington's disease, and hemophilia )
Latent (variations found in coding and regulatory regions, are not harmful on their own, and the change in each gene only becomes apparent under certain conditions e.g. susceptibility to lung cancer)
TYPES OF SNP
NON-CODING REGION
A segment of DNA that does comprise a gene and thus does not code for a protein .
CODING REGION
Regions of DNA/RNA sequences that code for proteins
Synonymous
A SNP in which both forms lead to the same polypeptide sequence is termed synonymous
(sometimes called a silent mutation).
Non synonymous
If a different polypeptide sequence is produced they are non synonymous . A non synonymous change may either be missense or nonsense, where a missense change results in a different amino acid, while a nonsense change results in a premature stop codon.
SNP Applications
• Gene discovery and mapping
• Association-based candidate polymorphism testing
• Diagnostics/risk profiling
• Response prediction
• Homogeneity testing/study design
• Gene function identification
Protein Sequence, Structure, and Functional Databases: UniProtKB, Swiss-Prot, TrEMBL, PIR, MIPS, PROSITE, PRINTS, BLOCKS, Pfam, NDRB, OWL, PDB, SCOP, CATH, NDB, PQS, SYSTERS, and Motif. Presented at UGC Sponsored National Workshop on Bioinformatics and Sequence Analysis conducted by Nesamony Memorial Christian College, Marthandam on 9th and 10th October, 2017 by Prof. T. Ashok Kumar
Bioinformatics in biotechnology by kk sahu KAUSHAL SAHU
Introduction
Bioinformatics – definition
History
Required skills
Core areas of bioinformatics
Components of bioinformatics
Nomenclature system in bioinformatics
Biological databases
Types of database
Bioinformatics tools
Applications of bioinformatics
Conclusion
References
It is a comprehensive, authoritative and timely knowledgebase of human genes and genetic disorders compiled to support human genetics research and education and the practice of clinical genetics.
One of the best websites for detailed and updated information of genetic diseases.
Set up in 1995 by the National Centre for Biotechnology Information (NCBI).
As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data.
Applications of genomics and proteomics pptIbad khan
Applications of genomics and proteomics ppt
genomics and proteomics ppt
in the field of health genomics and proteomics ppt
oncology ppt
biomedical application of genomics and proteomics ppt
agriculture application of genomics and proteomics ppt
proteomics in agriculture ppt
diagnosis of infectious disease ppt
personalized medicine ppt
Metabolites have various functions, including fuel, structure, signaling, stimulatory and inhibitory effects on enzymes, catalytic activity of their own (usually as a cofactor to an enzyme), defense, and interactions with other organisms (e.g. pigments, odorants, and pheromones).
Metabolome refers to the complete set of chemical compounds involved in an organism's metabolism (such as metabolic intermediates, hormones and other signaling molecules, and secondary metabolites)
Metabolomics is the scientific study of chemical processes involving metabolites. Metabolomics is a relatively new member to the ‘-omics’ family of systems biology technologies.
Composite: It compile and filter sequence data from primary database.
Specialized : database—allows targeted searching on one or more specific subject areas
whole genome analysis
history
needs
steps involved
human genome data
NGS
pyrosequencing
illumina
SOLiD
Ion torrent
PacBio
applications
problems
benefits
Slides contain information about why bioinformatics appeared,
who bioinformaticians are, what they do, what kind of cool applications and challenges in bioinformatics there are.
Slides were prepared for the Bioinformatics seminar 2016, Institute of Computer Science, University of Tartu.
Single Nucleotide Polymorphism (SNP)
Polymorphism is a generic term that means 'many shapes‘. It is the ability to appsear in different form .
A single nucleotide polymorphism (SNP) is a DNA sequence variation occurring when a single nucleotide - A, T, C, or G - in the genome differs between members of a species (or between paired chromosomes in an individual).
For example, two sequenced DNA fragments from different individuals, AAGCCTA to AAGCTTA, contain a difference in a single nucleotide. For a variation to be considered a SNP, it must occur in at least 1% of the population.
CHARACTERISTICS OF SNP
• In human beings, 99.9 percent bases are same.
• Remaining 0.1 percent makes a person unique.
• Different attributes / characteristics / traits
• How a person looks, diseases he or she develops.
These variations can be:
Harmless (change in phenotype)
Harmful (diabetes, cancer, heart disease, Huntington's disease, and hemophilia )
Latent (variations found in coding and regulatory regions, are not harmful on their own, and the change in each gene only becomes apparent under certain conditions e.g. susceptibility to lung cancer)
TYPES OF SNP
NON-CODING REGION
A segment of DNA that does comprise a gene and thus does not code for a protein .
CODING REGION
Regions of DNA/RNA sequences that code for proteins
Synonymous
A SNP in which both forms lead to the same polypeptide sequence is termed synonymous
(sometimes called a silent mutation).
Non synonymous
If a different polypeptide sequence is produced they are non synonymous . A non synonymous change may either be missense or nonsense, where a missense change results in a different amino acid, while a nonsense change results in a premature stop codon.
SNP Applications
• Gene discovery and mapping
• Association-based candidate polymorphism testing
• Diagnostics/risk profiling
• Response prediction
• Homogeneity testing/study design
• Gene function identification
Protein Sequence, Structure, and Functional Databases: UniProtKB, Swiss-Prot, TrEMBL, PIR, MIPS, PROSITE, PRINTS, BLOCKS, Pfam, NDRB, OWL, PDB, SCOP, CATH, NDB, PQS, SYSTERS, and Motif. Presented at UGC Sponsored National Workshop on Bioinformatics and Sequence Analysis conducted by Nesamony Memorial Christian College, Marthandam on 9th and 10th October, 2017 by Prof. T. Ashok Kumar
Bioinformatics in biotechnology by kk sahu KAUSHAL SAHU
Introduction
Bioinformatics – definition
History
Required skills
Core areas of bioinformatics
Components of bioinformatics
Nomenclature system in bioinformatics
Biological databases
Types of database
Bioinformatics tools
Applications of bioinformatics
Conclusion
References
It is a comprehensive, authoritative and timely knowledgebase of human genes and genetic disorders compiled to support human genetics research and education and the practice of clinical genetics.
One of the best websites for detailed and updated information of genetic diseases.
Set up in 1995 by the National Centre for Biotechnology Information (NCBI).
As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data.
Applications of genomics and proteomics pptIbad khan
Applications of genomics and proteomics ppt
genomics and proteomics ppt
in the field of health genomics and proteomics ppt
oncology ppt
biomedical application of genomics and proteomics ppt
agriculture application of genomics and proteomics ppt
proteomics in agriculture ppt
diagnosis of infectious disease ppt
personalized medicine ppt
Metabolites have various functions, including fuel, structure, signaling, stimulatory and inhibitory effects on enzymes, catalytic activity of their own (usually as a cofactor to an enzyme), defense, and interactions with other organisms (e.g. pigments, odorants, and pheromones).
Metabolome refers to the complete set of chemical compounds involved in an organism's metabolism (such as metabolic intermediates, hormones and other signaling molecules, and secondary metabolites)
Metabolomics is the scientific study of chemical processes involving metabolites. Metabolomics is a relatively new member to the ‘-omics’ family of systems biology technologies.
Composite: It compile and filter sequence data from primary database.
Specialized : database—allows targeted searching on one or more specific subject areas
whole genome analysis
history
needs
steps involved
human genome data
NGS
pyrosequencing
illumina
SOLiD
Ion torrent
PacBio
applications
problems
benefits
Slides contain information about why bioinformatics appeared,
who bioinformaticians are, what they do, what kind of cool applications and challenges in bioinformatics there are.
Slides were prepared for the Bioinformatics seminar 2016, Institute of Computer Science, University of Tartu.
Next generation genomics: Petascale data in the life sciencesGuy Coates
Keynote presentation at OGF 28.
The year 2000 saw the release of "The" human genome, the product of a the combined sequencing effort of the whole planet. In 2010, single institutions are sequencing thousands of genomes a year, producing petabytes of data. Furthermore, many of the large scale sequencing projects are based around international collaboration and consortia. The talk will explore how Grid and Cloud technologies are being used to share genomics data around the planet, revolutionizing life science research.
Centralized Model Organism Database (Biocuration 2014 poster)Andrew Su
A Centralized Model Organism Database (CMOD) for the Long Tail of Genomes
Presented at Biocuration 2014 in Toronto http://biocuration2014.events.oicr.on.ca/
See related slides at http://www.slideshare.net/andrewsu/20140116-gmod-short
BauhinaGenome.hk slides used for a school visit to talk DNA, genomics and Bauhinia to year 6 (11-12 year old) science class at the CIS school in Hong Kong.
Bioinformatics relevance with biotechnologyKAUSHAL SAHU
SYNOPSIS –
INTRODUCTION
HISTORY
NEED OF BIOINFORMATICS FOR THE GROWTH OF BIOTECHNOLOGY
HOW IS COMPUTING CHANGING BIOLOGY?
WHAT KIND OF DATA IS USED?
HOW DOES SEQUENCE ALIGNMENT WORK?
WHAT ARE THE ADVANTAGES OF USING COMPUTERS?
WHY IT’S USEFUL?
SCOPE OF BIOINFORMATICS IN INDIA
CONCLUSION
REFERENCE
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
1. Bioinformatics:
What, Why and
Where?
Mohamed El-Hadidi
Assistant Professor of Bioinformatics
Biomedical Informatics Program Director
School of Information Technology and Computer Science
Nile University
2. Where DNA is Located in our Body?
6/3/2020 Bioinformatics: What, Why and Where? 2
3. From Human Body to DNA Sequences
DNA Sequencers
Sequence Files
How many cells
in the Human
Body?
10 Trillion Cells!
6/3/2020 Bioinformatics: What, Why and Where? 3
4. From Human Body to DNA Sequences
DNA Sequencers
Sequence Files
How many
chromosomes in one
cell?
46
Chromosomes!
6/3/2020 4Bioinformatics: What, Why and Where?
5. From Human Body to DNA Sequences
DNA Sequencers
Sequence Files
What is the length of
all chromosomes in
one cell?
2 m in one cell!
1500 times from Earth to
moon (all cells)
6/3/2020 5Bioinformatics: What, Why and Where?
6. From Human Body to DNA Sequences
DNA Sequencers
Sequence Files
What are in
these files?
GAATTTGGGCAAGAATCCAGGCATTGGAACTTATTCAAATAACTAGTTTGCCTGTAATTTTCACTTTTTC
AGAGTCATCTGATAAAGCTTTCTTGCTACACATTTAGATAGATACACTCAATCCAGTTGTCTAGAAAGTT
CCCTGAGCCAGCTGGGAGCAGGAGGGGTAGTTGGGGCCAGGAATATTGGGGGTGTGTTTACTGAGCCCCT
AGAAAGTAAGTGCTAGATTTGACATTTCAATCCCTGAAGGCCCTGAAGTTCAGTATCAAATGACTGGTCC
TGTGGACTGAGCATCTGTGAATTGCATATGCTTAGAGTAAATTTTACTCCTACCAGTTTCAGCAGCTTGC
TTTAGCAAGCAGTATGGAAACACTAACATGGGGGAGTAGAATTTCTCTCTCTGATCCAAGTTTTATCTCA
TTCTGGTGGGTTTTCAAGGAGAGACTCGGAGTCCAAGTGTCCTTTCTGAATATATCTGGAACTTCTCATT
AACAAAAGACTCAAGTTATAATTTAGGGGACAAGGCACCCAATGAGAATGCCTTGCAGGCAGCCCTAAGT
ACACCTGCAATTACACCATTACTAGCGCGGCAGCACACATGGCCCTGACTTAGTTTAAATAATTACGTAA
GTCAACCATGATTGTTTGCCCTTTGCATAGAAGGGCAAGTATTGGTACCTGTTACAACTTAGGCTTTTTT
TTCTTTATGTTTGAGCCATGATGAGTGATTTACACTGTTGCATCCATATGTTGAGATGTAAGAATAAATT
AGACTTGGTAATTGCCCTTAAGTGTCTGGAAGTCAACTGGGGAAAGAGAGCTAGAGATAATAAGTGTGAA
ACAATGTCACAGAATCAATGACGGAACTCTTCCCAGGACAAAGGATGACTTTTGAGTTCAGTCTTTGCCT
TTAATTCTACATGGGGAGGAGAGCACGTTTAGCCACAAATGGAAGGGATTACTCATTTGAGCTATTTGGT
TATATGATTATTTCCCCAGAGAATAGGATGTGCAGGGCATTACACAAGCAGTGCCAATAGCAGCAAAGTT
CTTGAGAGTGCTAGTAATTCAAATGGCAGGAAGAGAAGGAATAAATGGTAAGGCTACCTACAGTTCACAG
AGAGCTCCATCCTCACTGTGGCTTTGGATTTTGTCCTGTGTGAAAGAGAAGTGACTGTGAACTGACATGC
TGTGTTTGGTGTTTTAGAAAGATGGCTGCAGCAGCGGTTTGGGGAATGGACTGCAGGAGTGGCATTGGAA
ACAGGAAGGTTCATGACTATTGCCAGAGACAGAGGATGAAGCAGGAGCAAGGAAGATTCAGGACAGGGGA
CTCCGGGGCTGATCAGGAGGCAGAACTGGTTGATAAGTATATGTAGCAGCATAAGAAAGAAAGAATCCCA
GATTGACACCCAGGCTTCTCACTTGGAAGCCTGGATAGATACTGAATGCAATCACAAAGGCTGGGAAGTC
AATGGGACTGCAGGGAAGGGAAGGGAAGGGAGGAGAAGAGGAAGGGCAGGAGGGTCCAATATCAATATTC
AGCTTTTAGATGTGTTGAGCTTGAAGTGCTCAGATGGAGAAGTCCAGGAGGCAGTAGAATACGGTGGTCC
AGAGCACAGGAGAGCAATGTGGCTTGAGTTGTCATTTGCTCACATATTTCCGTGTCAGTTACTTGTCTTA
GATCACAGAACAAGTTCTCCTCTCACAGTTTCCTGGCTCCACCTGTCTCATGCTCACCGTCAGCATCGAA
ATTGAGCCACACCAGGGGTTCTGGATACCAGCTTCTCTCTAGGTGAGGCTGCTATAGTCAGCAGCTGATT
AGTTGCAGTTATCAGCAACTGGTAATATAATATATTGTGCATATAAGTGTACCAGAAGTCATGTTTATAT
ATTGCTGCAAATACTCGGAATGGGGATCTCTTGTTCCCTGCTTAAGACCACATCACATTACTTGGTTTTG
TACGCTAGTGGCTGAACCAAAAAAAGTAGGAGATGATTTTTTTTCTTTTTTCTTAAAGCAGTAGCTTTTG
AACCTTGACCATGCTTTCTAACCAGCTGAGGGGCTTTTGAAAAAGAGGGTGCCTTACTGTGCCCCAGACC
AGGACAATCAGTATTTCTGGGGAATGGAGCCTGGCACACACACATTTCTTAAAGCTCCCTTGGCAATTCT
GAGGAGTGGATTACATGTTGTATGTAGCTCGTAACGAAAGAAATCTTGTCTTTGCTCTCAGACCCCCATT
TCTTACTCATCTCATGAGCTCCTTCGAGATCCAGAAACAGTTGCATATTTCATTAGTAAATCAGTTCCAG
AGTCACATTTTATTTCACAAGTTAGTCCATTAAAAGTTTCCTGCAGTGAGGAAATAGCCAGAAAGAACAC
TCCACCCCTCCTCCTTTTTATAACTATAGGGTCTGGCTCGACAGAGCAGGAGCATCGCCATCTTGGACAA
6/3/2020 6Bioinformatics: What, Why and Where?
7. From Human Body to DNA Sequences
DNA Sequencers
Sequence Files
What are in
these files?
GAATTTGGGCAAGAATCCAGGCATTGGAACTTATTCAAATAACTAGTTTGCCTGTAATTTTCACTTTTTC
AGAGTCATCTGATAAAGCTTTCTTGCTACACATTTAGATAGATACACTCAATCCAGTTGTCTAGAAAGTT
CCCTGAGCCAGCTGGGAGCAGGAGGGGTAGTTGGGGCCAGGAATATTGGGGGTGTGTTTACTGAGCCCCT
AGAAAGTAAGTGCTAGATTTGACATTTCAATCCCTGAAGGCCCTGAAGTTCAGTATCAAATGACTGGTCC
TGTGGACTGAGCATCTGTGAATTGCATATGCTTAGAGTAAATTTTACTCCTACCAGTTTCAGCAGCTTGC
TTTAGCAAGCAGTATGGAAACACTAACATGGGGGAGTAGAATTTCTCTCTCTGATCCAAGTTTTATCTCA
TTCTGGTGGGTTTTCAAGGAGAGACTCGGAGTCCAAGTGTCCTTTCTGAATATATCTGGAACTTCTCATT
AACAAAAGACTCAAGTTATAATTTAGGGGACAAGGCACCCAATGAGAATGCCTTGCAGGCAGCCCTAAGT
ACACCTGCAATTACACCATTACTAGCGCGGCAGCACACATGGCCCTGACTTAGTTTAAATAATTACGTAA
GTCAACCATGATTGTTTGCCCTTTGCATAGAAGGGCAAGTATTGGTACCTGTTACAACTTAGGCTTTTTT
TTCTTTATGTTTGAGCCATGATGAGTGATTTACACTGTTGCATCCATATGTTGAGATGTAAGAATAAATT
AGACTTGGTAATTGCCCTTAAGTGTCTGGAAGTCAACTGGGGAAAGAGAGCTAGAGATAATAAGTGTGAA
ACAATGTCACAGAATCAATGACGGAACTCTTCCCAGGACAAAGGATGACTTTTGAGTTCAGTCTTTGCCT
TTAATTCTACATGGGGAGGAGAGCACGTTTAGCCACAAATGGAAGGGATTACTCATTTGAGCTATTTGGT
TATATGATTATTTCCCCAGAGAATAGGATGTGCAGGGCATTACACAAGCAGTGCCAATAGCAGCAAAGTT
CTTGAGAGTGCTAGTAATTCAAATGGCAGGAAGAGAAGGAATAAATGGTAAGGCTACCTACAGTTCACAG
AGAGCTCCATCCTCACTGTGGCTTTGGATTTTGTCCTGTGTGAAAGAGAAGTGACTGTGAACTGACATGC
TGTGTTTGGTGTTTTAGAAAGATGGCTGCAGCAGCGGTTTGGGGAATGGACTGCAGGAGTGGCATTGGAA
ACAGGAAGGTTCATGACTATTGCCAGAGACAGAGGATGAAGCAGGAGCAAGGAAGATTCAGGACAGGGGA
CTCCGGGGCTGATCAGGAGGCAGAACTGGTTGATAAGTATATGTAGCAGCATAAGAAAGAAAGAATCCCA
GATTGACACCCAGGCTTCTCACTTGGAAGCCTGGATAGATACTGAATGCAATCACAAAGGCTGGGAAGTC
AATGGGACTGCAGGGAAGGGAAGGGAAGGGAGGAGAAGAGGAAGGGCAGGAGGGTCCAATATCAATATTC
AGCTTTTAGATGTGTTGAGCTTGAAGTGCTCAGATGGAGAAGTCCAGGAGGCAGTAGAATACGGTGGTCC
AGAGCACAGGAGAGCAATGTGGCTTGAGTTGTCATTTGCTCACATATTTCCGTGTCAGTTACTTGTCTTA
GATCACAGAACAAGTTCTCCTCTCACAGTTTCCTGGCTCCACCTGTCTCATGCTCACCGTCAGCATCGAA
ATTGAGCCACACCAGGGGTTCTGGATACCAGCTTCTCTCTAGGTGAGGCTGCTATAGTCAGCAGCTGATT
AGTTGCAGTTATCAGCAACTGGTAATATAATATATTGTGCATATAAGTGTACCAGAAGTCATGTTTATAT
ATTGCTGCAAATACTCGGAATGGGGATCTCTTGTTCCCTGCTTAAGACCACATCACATTACTTGGTTTTG
TACGCTAGTGGCTGAACCAAAAAAAGTAGGAGATGATTTTTTTTCTTTTTTCTTAAAGCAGTAGCTTTTG
AACCTTGACCATGCTTTCTAACCAGCTGAGGGGCTTTTGAAAAAGAGGGTGCCTTACTGTGCCCCAGACC
AGGACAATCAGTATTTCTGGGGAATGGAGCCTGGCACACACACATTTCTTAAAGCTCCCTTGGCAATTCT
GAGGAGTGGATTACATGTTGTATGTAGCTCGTAACGAAAGAAATCTTGTCTTTGCTCTCAGACCCCCATT
TCTTACTCATCTCATGAGCTCCTTCGAGATCCAGAAACAGTTGCATATTTCATTAGTAAATCAGTTCCAG
AGTCACATTTTATTTCACAAGTTAGTCCATTAAAAGTTTCCTGCAGTGAGGAAATAGCCAGAAAGAACAC
TCCACCCCTCCTCCTTTTTATAACTATAGGGTCTGGCTCGACAGAGCAGGAGCATCGCCATCTTGGACAA
6/3/2020 7Bioinformatics: What, Why and Where?
8. From Human Body to DNA Sequences
DNA Sequencers
Sequence Files
GAATTTGGGCAAGAATCCAGGCATTGGAACTTATTCAAATAACTAGTTTGCCTGTAATTTTCACTTTTTC
AGAGTCATCTGATAAAGCTTTCTTGCTACACATTTAGATAGATACACTCAATCCAGTTGTCTAGAAAGTT
CCCTGAGCCAGCTGGGAGCAGGAGGGGTAGTTGGGGCCAGGAATATTGGGGGTGTGTTTACTGAGCCCCT
AGAAAGTAAGTGCTAGATTTGACATTTCAATCCCTGAAGGCCCTGAAGTTCAGTATCAAATGACTGGTCC
TGTGGACTGAGCATCTGTGAATTGCATATGCTTAGAGTAAATTTTACTCCTACCAGTTTCAGCAGCTTGC
TTTAGCAAGCAGTATGGAAACACTAACATGGGGGAGTAGAATTTCTCTCTCTGATCCAAGTTTTATCTCA
TTCTGGTGGGTTTTCAAGGAGAGACTCGGAGTCCAAGTGTCCTTTCTGAATATATCTGGAACTTCTCATT
AACAAAAGACTCAAGTTATAATTTAGGGGACAAGGCACCCAATGAGAATGCCTTGCAGGCAGCCCTAAGT
ACACCTGCAATTACACCATTACTAGCGCGGCAGCACACATGGCCCTGACTTAGTTTAAATAATTACGTAA
GTCAACCATGATTGTTTGCCCTTTGCATAGAAGGGCAAGTATTGGTACCTGTTACAACTTAGGCTTTTTT
TTCTTTATGTTTGAGCCATGATGAGTGATTTACACTGTTGCATCCATATGTTGAGATGTAAGAATAAATT
AGACTTGGTAATTGCCCTTAAGTGTCTGGAAGTCAACTGGGGAAAGAGAGCTAGAGATAATAAGTGTGAA
ACAATGTCACAGAATCAATGACGGAACTCTTCCCAGGACAAAGGATGACTTTTGAGTTCAGTCTTTGCCT
TTAATTCTACATGGGGAGGAGAGCACGTTTAGCCACAAATGGAAGGGATTACTCATTTGAGCTATTTGGT
TATATGATTATTTCCCCAGAGAATAGGATGTGCAGGGCATTACACAAGCAGTGCCAATAGCAGCAAAGTT
CTTGAGAGTGCTAGTAATTCAAATGGCAGGAAGAGAAGGAATAAATGGTAAGGCTACCTACAGTTCACAG
AGAGCTCCATCCTCACTGTGGCTTTGGATTTTGTCCTGTGTGAAAGAGAAGTGACTGTGAACTGACATGC
TGTGTTTGGTGTTTTAGAAAGATGGCTGCAGCAGCGGTTTGGGGAATGGACTGCAGGAGTGGCATTGGAA
ACAGGAAGGTTCATGACTATTGCCAGAGACAGAGGATGAAGCAGGAGCAAGGAAGATTCAGGACAGGGGA
CTCCGGGGCTGATCAGGAGGCAGAACTGGTTGATAAGTATATGTAGCAGCATAAGAAAGAAAGAATCCCA
GATTGACACCCAGGCTTCTCACTTGGAAGCCTGGATAGATACTGAATGCAATCACAAAGGCTGGGAAGTC
AATGGGACTGCAGGGAAGGGAAGGGAAGGGAGGAGAAGAGGAAGGGCAGGAGGGTCCAATATCAATATTC
AGCTTTTAGATGTGTTGAGCTTGAAGTGCTCAGATGGAGAAGTCCAGGAGGCAGTAGAATACGGTGGTCC
AGAGCACAGGAGAGCAATGTGGCTTGAGTTGTCATTTGCTCACATATTTCCGTGTCAGTTACTTGTCTTA
GATCACAGAACAAGTTCTCCTCTCACAGTTTCCTGGCTCCACCTGTCTCATGCTCACCGTCAGCATCGAA
ATTGAGCCACACCAGGGGTTCTGGATACCAGCTTCTCTCTAGGTGAGGCTGCTATAGTCAGCAGCTGATT
AGTTGCAGTTATCAGCAACTGGTAATATAATATATTGTGCATATAAGTGTACCAGAAGTCATGTTTATAT
ATTGCTGCAAATACTCGGAATGGGGATCTCTTGTTCCCTGCTTAAGACCACATCACATTACTTGGTTTTG
TACGCTAGTGGCTGAACCAAAAAAAGTAGGAGATGATTTTTTTTCTTTTTTCTTAAAGCAGTAGCTTTTG
AACCTTGACCATGCTTTCTAACCAGCTGAGGGGCTTTTGAAAAAGAGGGTGCCTTACTGTGCCCCAGACC
AGGACAATCAGTATTTCTGGGGAATGGAGCCTGGCACACACACATTTCTTAAAGCTCCCTTGGCAATTCT
GAGGAGTGGATTACATGTTGTATGTAGCTCGTAACGAAAGAAATCTTGTCTTTGCTCTCAGACCCCCATT
TCTTACTCATCTCATGAGCTCCTTCGAGATCCAGAAACAGTTGCATATTTCATTAGTAAATCAGTTCCAG
AGTCACATTTTATTTCACAAGTTAGTCCATTAAAAGTTTCCTGCAGTGAGGAAATAGCCAGAAAGAACAC
TCCACCCCTCCTCCTTTTTATAACTATAGGGTCTGGCTCGACAGAGCAGGAGCATCGCCATCTTGGACAA
How many
nucleotides in the
Human body?
3 Billion
Nucleotides!
6/3/2020 8Bioinformatics: What, Why and Where?
9. From Human Body to DNA Sequences
DNA Sequencers
Sequence Files
What is the size
of data?
150 GB/person
6/3/2020 9Bioinformatics: What, Why and Where?
10. How These Files were Generated?
6/3/2020 Bioinformatics: What, Why and Where? 10
11. How These Files were Generated?
6/3/2020 Bioinformatics: What, Why and Where? 11
12. Bioinformatics Data is
Increasing Rapidly!
• Speed of sequencing?
10,000 bp/day/machine ->
billions bp/day/machine.
• Computing cost and time?
Sequencing cost is falling 5X
faster than computing
• Price / genome?
Dropped to $1000!
• Storage cost?
150 GB/genome
Bioinformatics: What, Why and Where? 12
How These Files were Generated?
15. How to Make Sense of This BIG DATA?
Through Bioinformatics!
What is Bioinformatics??!
6/3/2020 Bioinformatics: What, Why and Where? 15
16. What Do You Need to Learn Bioinformatics?
6/3/2020 Bioinformatics: What, Why and Where? 16
Statistics
Computer
Science
Biology
Bioinformatics
Data
Science
Biostatistics Computational
Biology
20. What is Bioinformatics?
6/3/2020 Bioinformatics: What, Why and Where? 20
GAATTTGGGCAAGAATCCAGGCATTGGAACTTATTCAAATAACTAGTTTGCCTGTAATTTTCACTTTTTC
AGAGTCATCTGATAAAGCTTTCTTGCTACACATTTAGATAGATACACTCAATCCAGTTGTCTAGAAAGTT
CCCTGAGCCAGCTGGGAGCAGGAGGGGTAGTTGGGGCCAGGAATATTGGGGGTGTGTTTACTGAGCCCCT
AGAAAGTAAGTGCTAGATTTGACATTTCAATCCCTGAAGGCCCTGAAGTTCAGTATCAAATGACTGGTCC
TGTGGACTGAGCATCTGTGAATTGCATATGCTTAGAGTAAATTTTACTCCTACCAGTTTCAGCAGCTTGC
TTTAGCAAGCAGTATGGAAACACTAACATGGGGGAGTAGAATTTCTCTCTCTGATCCAAGTTTTATCTCA
TTCTGGTGGGTTTTCAAGGAGAGACTCGGAGTCCAAGTGTCCTTTCTGAATATATCTGGAACTTCTCATT
AACAAAAGACTCAAGTTATAATTTAGGGGACAAGGCACCCAATGAGAATGCCTTGCAGGCAGCCCTAAGT
ACACCTGCAATTACACCATTACTAGCGCGGCAGCACACATGGCCCTGACTTAGTTTAAATAATTACGTAA
GTCAACCATGATTGTTTGCCCTTTGCATAGAAGGGCAAGTATTGGTACCTGTTACAACTTAGGCTTTTTT
TTCTTTATGTTTGAGCCATGATGAGTGATTTACACTGTTGCATCCATATGTTGAGATGTAAGAATAAATT
AGACTTGGTAATTGCCCTTAAGTGTCTGGAAGTCAACTGGGGAAAGAGAGCTAGAGATAATAAGTGTGAA
ACAATGTCACAGAATCAATGACGGAACTCTTCCCAGGACAAAGGATGACTTTTGAGTTCAGTCTTTGCCT
TTAATTCTACATGGGGAGGAGAGCACGTTTAGCCACAAATGGAAGGGATTACTCATTTGAGCTATTTGGT
TATATGATTATTTCCCCAGAGAATAGGATGTGCAGGGCATTACACAAGCAGTGCCAATAGCAGCAAAGTT
CTTGAGAGTGCTAGTAATTCAAATGGCAGGAAGAGAAGGAATAAATGGTAAGGCTACCTACAGTTCACAG
AGAGCTCCATCCTCACTGTGGCTTTGGATTTTGTCCTGTGTGAAAGAGAAGTGACTGTGAACTGACATGC
TGTGTTTGGTGTTTTAGAAAGATGGCTGCAGCAGCGGTTTGGGGAATGGACTGCAGGAGTGGCATTGGAA
ACAGGAAGGTTCATGACTATTGCCAGAGACAGAGGATGAAGCAGGAGCAAGGAAGATTCAGGACAGGGGA
CTCCGGGGCTGATCAGGAGGCAGAACTGGTTGATAAGTATATGTAGCAGCATAAGAAAGAAAGAATCCCA
GATTGACACCCAGGCTTCTCACTTGGAAGCCTGGATAGATACTGAATGCAATCACAAAGGCTGGGAAGTC
AATGGGACTGCAGGGAAGGGAAGGGAAGGGAGGAGAAGAGGAAGGGCAGGAGGGTCCAATATCAATATTC
AGCTTTTAGATGTGTTGAGCTTGAAGTGCTCAGATGGAGAAGTCCAGGAGGCAGTAGAATACGGTGGTCC
AGAGCACAGGAGAGCAATGTGGCTTGAGTTGTCATTTGCTCACATATTTCCGTGTCAGTTACTTGTCTTA
GATCACAGAACAAGTTCTCCTCTCACAGTTTCCTGGCTCCACCTGTCTCATGCTCACCGTCAGCATCGAA
ATTGAGCCACACCAGGGGTTCTGGATACCAGCTTCTCTCTAGGTGAGGCTGCTATAGTCAGCAGCTGATT
AGTTGCAGTTATCAGCAACTGGTAATATAATATATTGTGCATATAAGTGTACCAGAAGTCATGTTTATAT
ATTGCTGCAAATACTCGGAATGGGGATCTCTTGTTCCCTGCTTAAGACCACATCACATTACTTGGTTTTG
TACGCTAGTGGCTGAACCAAAAAAAGTAGGAGATGATTTTTTTTCTTTTTTCTTAAAGCAGTAGCTTTTG
AACCTTGACCATGCTTTCTAACCAGCTGAGGGGCTTTTGAAAAAGAGGGTGCCTTACTGTGCCCCAGACC
AGGACAATCAGTATTTCTGGGGAATGGAGCCTGGCACACACACATTTCTTAAAGCTCCCTTGGCAATTCT
GAGGAGTGGATTACATGTTGTATGTAGCTCGTAACGAAAGAAATCTTGTCTTTGCTCTCAGACCCCCATT
TCTTACTCATCTCATGAGCTCCTTCGAGATCCAGAAACAGTTGCATATTTCATTAGTAAATCAGTTCCAG
AGTCACATTTTATTTCACAAGTTAGTCCATTAAAAGTTTCCTGCAGTGAGGAAATAGCCAGAAAGAACAC
TCCACCCCTCCTCCTTTTTATAACTATAGGGTCTGGCTCGACAGAGCAGGAGCATCGCCATCTTGGACAA
Use Existing tools to build
analysis workflows
• Linux
• Command Line
• Scripting
Develop your own tools
• Programming
• Algorithm Design
• Machine Learning
21. What is Bioinformatics?
6/3/2020 Bioinformatics: What, Why and Where? 21
GAATTTGGGCAAGAATCCAGGCATTGGAACTTATTCAAATAACTAGTTTGCCTGTAATTTTCACTTTTTC
AGAGTCATCTGATAAAGCTTTCTTGCTACACATTTAGATAGATACACTCAATCCAGTTGTCTAGAAAGTT
CCCTGAGCCAGCTGGGAGCAGGAGGGGTAGTTGGGGCCAGGAATATTGGGGGTGTGTTTACTGAGCCCCT
AGAAAGTAAGTGCTAGATTTGACATTTCAATCCCTGAAGGCCCTGAAGTTCAGTATCAAATGACTGGTCC
TGTGGACTGAGCATCTGTGAATTGCATATGCTTAGAGTAAATTTTACTCCTACCAGTTTCAGCAGCTTGC
TTTAGCAAGCAGTATGGAAACACTAACATGGGGGAGTAGAATTTCTCTCTCTGATCCAAGTTTTATCTCA
TTCTGGTGGGTTTTCAAGGAGAGACTCGGAGTCCAAGTGTCCTTTCTGAATATATCTGGAACTTCTCATT
AACAAAAGACTCAAGTTATAATTTAGGGGACAAGGCACCCAATGAGAATGCCTTGCAGGCAGCCCTAAGT
ACACCTGCAATTACACCATTACTAGCGCGGCAGCACACATGGCCCTGACTTAGTTTAAATAATTACGTAA
GTCAACCATGATTGTTTGCCCTTTGCATAGAAGGGCAAGTATTGGTACCTGTTACAACTTAGGCTTTTTT
TTCTTTATGTTTGAGCCATGATGAGTGATTTACACTGTTGCATCCATATGTTGAGATGTAAGAATAAATT
AGACTTGGTAATTGCCCTTAAGTGTCTGGAAGTCAACTGGGGAAAGAGAGCTAGAGATAATAAGTGTGAA
ACAATGTCACAGAATCAATGACGGAACTCTTCCCAGGACAAAGGATGACTTTTGAGTTCAGTCTTTGCCT
TTAATTCTACATGGGGAGGAGAGCACGTTTAGCCACAAATGGAAGGGATTACTCATTTGAGCTATTTGGT
TATATGATTATTTCCCCAGAGAATAGGATGTGCAGGGCATTACACAAGCAGTGCCAATAGCAGCAAAGTT
CTTGAGAGTGCTAGTAATTCAAATGGCAGGAAGAGAAGGAATAAATGGTAAGGCTACCTACAGTTCACAG
AGAGCTCCATCCTCACTGTGGCTTTGGATTTTGTCCTGTGTGAAAGAGAAGTGACTGTGAACTGACATGC
TGTGTTTGGTGTTTTAGAAAGATGGCTGCAGCAGCGGTTTGGGGAATGGACTGCAGGAGTGGCATTGGAA
ACAGGAAGGTTCATGACTATTGCCAGAGACAGAGGATGAAGCAGGAGCAAGGAAGATTCAGGACAGGGGA
CTCCGGGGCTGATCAGGAGGCAGAACTGGTTGATAAGTATATGTAGCAGCATAAGAAAGAAAGAATCCCA
GATTGACACCCAGGCTTCTCACTTGGAAGCCTGGATAGATACTGAATGCAATCACAAAGGCTGGGAAGTC
AATGGGACTGCAGGGAAGGGAAGGGAAGGGAGGAGAAGAGGAAGGGCAGGAGGGTCCAATATCAATATTC
AGCTTTTAGATGTGTTGAGCTTGAAGTGCTCAGATGGAGAAGTCCAGGAGGCAGTAGAATACGGTGGTCC
AGAGCACAGGAGAGCAATGTGGCTTGAGTTGTCATTTGCTCACATATTTCCGTGTCAGTTACTTGTCTTA
GATCACAGAACAAGTTCTCCTCTCACAGTTTCCTGGCTCCACCTGTCTCATGCTCACCGTCAGCATCGAA
ATTGAGCCACACCAGGGGTTCTGGATACCAGCTTCTCTCTAGGTGAGGCTGCTATAGTCAGCAGCTGATT
AGTTGCAGTTATCAGCAACTGGTAATATAATATATTGTGCATATAAGTGTACCAGAAGTCATGTTTATAT
ATTGCTGCAAATACTCGGAATGGGGATCTCTTGTTCCCTGCTTAAGACCACATCACATTACTTGGTTTTG
TACGCTAGTGGCTGAACCAAAAAAAGTAGGAGATGATTTTTTTTCTTTTTTCTTAAAGCAGTAGCTTTTG
AACCTTGACCATGCTTTCTAACCAGCTGAGGGGCTTTTGAAAAAGAGGGTGCCTTACTGTGCCCCAGACC
AGGACAATCAGTATTTCTGGGGAATGGAGCCTGGCACACACACATTTCTTAAAGCTCCCTTGGCAATTCT
GAGGAGTGGATTACATGTTGTATGTAGCTCGTAACGAAAGAAATCTTGTCTTTGCTCTCAGACCCCCATT
TCTTACTCATCTCATGAGCTCCTTCGAGATCCAGAAACAGTTGCATATTTCATTAGTAAATCAGTTCCAG
AGTCACATTTTATTTCACAAGTTAGTCCATTAAAAGTTTCCTGCAGTGAGGAAATAGCCAGAAAGAACAC
TCCACCCCTCCTCCTTTTTATAACTATAGGGTCTGGCTCGACAGAGCAGGAGCATCGCCATCTTGGACAA
Use Existing tools to build
analysis workflows
Develop your own tools
• Linux
• Command Line
• Scripting
• Programming
• Algorithm Design
• Machine Learning
A = 1765 G = 3561
C = 2677 T = 1121
22. What is Bioinformatics?
6/3/2020 Bioinformatics: What, Why and Where? 22
Use Existing tools to build
analysis workflows
Develop your own tools
• Linux
• Command Line
• Scripting
• Programming
• Algorithm Design
• Machine Learning
23. Biologist (Biology Background)
Use existing bioinformatics tools
Computer Scientist (CS Background)
Develops bioinformatics tools
Basic User
Windows OS
Web-based Tools
GUI Standalone tools
No Programming skills
Advanced User
Linux OS
Command line Standalone
tools
Basic Programming Skills
Developer
Basic Biology Knowledge
Advanced Programming Skills
Advanced Mathematics
Advanced Statistics
Who Can Be a Bioinformatician?
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24. How can I Learn Bioinformatics?
Tons of free courses are available online!
More than 26 million
results when searching
without comma!
6/3/2020 Bioinformatics: What, Why and Where? 24
25. How can I Learn Bioinformatics?
Tons of free courses are available online!
More than 46 million
results when searching
without comma!
6/3/2020 Bioinformatics: What, Why and Where? 25
26. Examples of Free Online Bioinformatics MOOCs
Websites
6/3/2020 Bioinformatics: What, Why and Where? 26
28. Milestones of
Bioinformatics
28
• OMICS Sciences
• Programming and Data
Structure
•Algorithm Design
• LINUX
• Statistics
•Basic Mathematics
• AI and Data Science
•Data Visualization
• Results Interpretation
38. 6/3/2020 Bioinformatics: What, Why and Where? 38
Institute/Company Department Sequencer
American University in Cairo (AUC) Biology Ion S5
American University in Cairo (AUC)
Global Health and Human
Ecology MiSeq
National Research Center (NRC) Genetics MiSeq
Zewail City of Science and Technology Center for Genomics
MiSeq and
NextSeq 500
Kasr Alainy School of Medicine Clinical Oncology 3 MiSeq
CCHE 57357 Genomics program
MiSeq and
NextSeq 500
Ahram Canadian University Central Research Lab
Agilent
Bioanalyzer 2100
National Research Center (NRC) Genetics Ion torrent
National Research Center (NRC) Environmental department Ion torrent PGM
MASRI ain shams University Center
Ion S5 and Ion
shef
Air forces specialised hospital Labs Miseq
Maadi military hospital Labs Ion S5
Mansoura University Stem cells center Ion torrent
National Cancer Institute (NCI) Molecular biology Ion S5
Abo Alraish Hospital Microbiology Labs MiSeq
Alexandria Regional Center for Women's Health
and Development Ion S5
Tanta University - Faculty of Medicine - Center of
Exellence Genomic Signature Center MiSeq
Magdi Yacoub Foundation
MiSeq and
NextSeq
Generations Genetics Labs MiSeq
Sequencers in Egypt
(Sample)
Source: Prof. Ahmed Moustafa, AUC.
39. What Bioinformatics Can Do for Life Sciences?
6/3/2020 Bioinformatics: What, Why and Where? 39
41. Gene Prediction
• Gene structure
• Open Reading Frames (ORFs).
• Start and stop of the gene
• Locations of exons and introns
• Splice variants
• Gene prediction is one of the first and
most important steps in understanding
any genome after being sequenced.
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42. Sequence Comparison
• Compare unknown gene or protein
sequences against known sequences to
identify their origin or function.
• Finding Signatures that can be used in
diagnostics
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43. Phylogenetic Analyses
• Evolutionary relationship among a
group of related molecules or
organisms
• Track gene flow based on sequence
similarity
6/3/2020 Bioinformatics: What, Why and Where? 43
44. Understand the Functions of Genes (Pathway
Analysis)
6/3/2020 Bioinformatics: What, Why and Where? 44
45. Predicting Protein Structure and Function
• Protein’s 3D structure Prediction
• Understand how biomolecules
interact with other molecules
• Predict functions based on
interactions
6/3/2020 Bioinformatics: What, Why and Where? 45
46. Drug Design
• It is faster to analyze molecules on
computer as compared to
experimental approaches.
• Helps in identifying drug
targets easily
• Simulating drug effects on computers
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48. Applications of
Bioinformatics in Medicine
• The Human Genome Project (HGP) helps scientists to
search for genes directly associated with diseases and
understand the molecular basis of those identified
diseases.
• This new Information will help in better understanding
of the mechanisms of diseases and hence develop
better treatment and preventive methods.
6/3/2020 Bioinformatics: What, Why and Where? 48
49. Applications of
Bioinformatics in Pharmacy
• Identification and validating new drugs through
Computer Aided Drug Design (CADD).
• Helps to develop specific drugs with less side
effect
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50. Applications of Bioinformatics
in Food Security
• Large amount of genomics data is available from plants and
animals
• Bioinformatic analysis of plant and animal genomes will
help scientists to improve crops
• Resistant to drought
• Resistant to insects and pests
• More nutritional value
• Animals with higher meat quality and productivity
6/3/2020 Bioinformatics: What, Why and Where? 50
51. Applications of Bioinformatics
in the Environment
• Sequencing and analysis of microbial genomes and search
for genes expressing enzymes for
• Bioremediation and biodegradation
• Climate change studies (Microbes that use CO2 as their
sole source of enegy)
• Alternative energy sources (energy from light)
• Microbes with industrial benefits
• Generation of Biogas
6/3/2020 Bioinformatics: What, Why and Where? 51
53. Take Home Messages
• Understand the biological background first (in details)!
• For writing a software
• For using a software
• Which tool/software to use?
• Understand the algorithm behind each software/tool
• Test different parameters
• Select the best tool
• Free software are everywhere
• Read about benchmarking studies first
• Before Writing your own software
• Check if it is exist (don’t work from scratch)
• Modify existing tools
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54. Biologists and Computer Scientitst Should
Communicate!
6/3/2020 Bioinformatics: What, Why and Where? 54