This document provides an introduction to the field of bioinformatics. It defines bioinformatics as the merging of biology, computer science, and information technology into a single discipline. The document outlines key topics in bioinformatics including what is bioinformatics, why it is needed due to the growth of sequencing data, common data types and analysis problems, careers in bioinformatics, and different sequencing technologies such as Illumina and SOLiD sequencing.
An introduction to bioinformatics practices and aims will be given and contrasted against approaches from other fields. Most importantly, it will be discussed how bioinformatics fits into the discovery cycle for hypothesis driven neuroscience research.
Slides for the afternoon session on "Introduction to Bioinformatics", delivered at the James Hutton Institute, 29th, 20th May and 5th June 2014, by Leighton Pritchard and Peter Cock.
Slides cover introductory guidance and links to resources, theory and use of BLAST tools, and a workshop featuring some common tools and tasks.
This HIBB presentation provides background information on bases, amino acids, proteins, nucleotides and DNA. The presentation then explains what bioinformatics is, lists some examples, and demonstrates some tools. It demonstrates tools which compare parts of human and chimp genes, and illustrate drug resistance analysis and HIV subtype analysis. It then discusses some ethical and clinical aspects to bioinformatics.
As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data.
An Introduction to Bioinformatics
Drexel University INFO648-900-200915
A Presentation of Health Informatics Group 5
Cecilia Vernes
Joel Abueg
Kadodjomon Yeo
Sharon McDowell Hall
Terrence Hughes
An introduction to bioinformatics practices and aims will be given and contrasted against approaches from other fields. Most importantly, it will be discussed how bioinformatics fits into the discovery cycle for hypothesis driven neuroscience research.
Slides for the afternoon session on "Introduction to Bioinformatics", delivered at the James Hutton Institute, 29th, 20th May and 5th June 2014, by Leighton Pritchard and Peter Cock.
Slides cover introductory guidance and links to resources, theory and use of BLAST tools, and a workshop featuring some common tools and tasks.
This HIBB presentation provides background information on bases, amino acids, proteins, nucleotides and DNA. The presentation then explains what bioinformatics is, lists some examples, and demonstrates some tools. It demonstrates tools which compare parts of human and chimp genes, and illustrate drug resistance analysis and HIV subtype analysis. It then discusses some ethical and clinical aspects to bioinformatics.
As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data.
An Introduction to Bioinformatics
Drexel University INFO648-900-200915
A Presentation of Health Informatics Group 5
Cecilia Vernes
Joel Abueg
Kadodjomon Yeo
Sharon McDowell Hall
Terrence Hughes
Uses of Artificial Intelligence in BioinformaticsPragya Pai
This presentation is about the usage of Artificial Intelligence in Bioinformatics. These slides give the basic knowledge about usage of Artificial Intelligence in Bioinformatics.
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.
Computational Biology and BioinformaticsSharif Shuvo
Computational Biology and Bioinformatics is a rapidly developing multi-disciplinary field. The systematic achievement of data made possible by genomics and proteomics technologies has created a tremendous gap between available data and their biological interpretation.
Basics of Data Analysis in BioinformaticsElena Sügis
Presentation gives introduction to the Basics of Data Analysis in Bioinformatics.
The following topics are covered:
Data acquisition
Data summary(selecting the needed column/rows from the file and showing basic descriptive statistics)
Preprocessing (missing values imputation, data normalization, etc.)
Principal Component Analysis
Data Clustering and cluster annotation (k-means, hierarchical)
Cluster annotations
This presentation, prepared by Gerry Lushington, is a friendly introduction to the basics of data mining, as applied to biological problems. The intended audience is students and scientific researchers from a non-computational background.
Uses of Artificial Intelligence in BioinformaticsPragya Pai
This presentation is about the usage of Artificial Intelligence in Bioinformatics. These slides give the basic knowledge about usage of Artificial Intelligence in Bioinformatics.
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.
Computational Biology and BioinformaticsSharif Shuvo
Computational Biology and Bioinformatics is a rapidly developing multi-disciplinary field. The systematic achievement of data made possible by genomics and proteomics technologies has created a tremendous gap between available data and their biological interpretation.
Basics of Data Analysis in BioinformaticsElena Sügis
Presentation gives introduction to the Basics of Data Analysis in Bioinformatics.
The following topics are covered:
Data acquisition
Data summary(selecting the needed column/rows from the file and showing basic descriptive statistics)
Preprocessing (missing values imputation, data normalization, etc.)
Principal Component Analysis
Data Clustering and cluster annotation (k-means, hierarchical)
Cluster annotations
This presentation, prepared by Gerry Lushington, is a friendly introduction to the basics of data mining, as applied to biological problems. The intended audience is students and scientific researchers from a non-computational background.
Journal of Applied Bioinformatics & Computational Biology (JABCB) promotes rigorous research that makes a significant contribution in advancing knowledge in the fields of Biology & Bioinformatics.
Data-integration platform for cancer research:cBioPortal demoCORBEL
Participants will be introduced to the data-integration platform cBioPortal. Here, different sources of research data (clinical, imaging, biosample and experimental) of a study are integrated, enabling viewing, querying and analysis.
This webinar is aimed at data managers, researchers, PhD students and postdocs involved in clinical, translational and biomedical research.
Improvements in sequencing technologies have led to a deluge of genomics data in many fields of research. Specifically, the increasing size of cancer-related genomics datasets require comprehensive software solutions that remain accessible to clinical researchers. Clearly, there is an obvious need for tools that integrate genomics and other molecular biology results with the phenotypic and clinical outcome data. During this webinar, the cBio Cancer Genomics Portal (cBioPortal) will be introduced through a practical use case.
The cBioPortal is an open source data integration platform that enables researchers to view, query, analyse and share complex genomic cancer datasets in a user-friendly manner. The platform was originally developed by Memorial Sloan Kettering Cancer Center (New York, USA)1 and is actively maintained and further developed by an international community. The original instance of cBioPortal (http://cbioportal.org) currently provides access to data from almost 83000 tumor samples from 273 public studies.
The demo will include:
· short introduction on the FAIR principles (Findable, Accessible, Interoperable, Reusable)
· navigation through a public study on the data-integration platform cBioPortal
· recreation of select plots from publications of interest using cBioPortal functionalities
The CORBEL webinar series aims to address challenges and share best practice between biological and medical research infrastructures. The series is aimed at technical operators of RIs and is aligned with the CORBEL competency framework.
Bioinformatics Course at Indian Biosciences and Research Instituteajay vishwakrma
Bioinformatics is the study of the inherent structure of biological information and biological systems. It brings together the avalanche of systematic biological data (e.g. genomes) with the analytic theory and practical tools of mathematics and computer science. Bioinformatics is a rapidly evolving and developing field both in terms of breadth of scope of useful applications and in terms of depth of what can be accomplished with the mission providing the training and knowledge in Bioinformatics IBRI has introduced the courses in Bioinformatics.
Bioinformatics: Bioinformatics, Healthcare Informatics and Analytics for Improved Healthcare System, Intelligent Monitoring and Control for Improved Healthcare System.
Bioinformatics: Introduction, Objective of Bioinformatics, Bioinformatics Databases, Concept of Bioinformatics, Impact of Bioinformatics in Vaccine Discovery
2014 CrossRef Annual Meeting Keynote: Ways and Needs to Promote Rapid Data Sh...Crossref
Keynote address: "Ways and Needs to Promote Rapid Data Sharing" by Laurie Goodman of GigaScience.
Data is the base upon which all scientific discoveries are built, and data availability speeds the rate at which discoveries are made. Given that the overall goal for research is to improve human health and our environment, waiting to release data until after the first publication (sometimes taking years) is unacceptable. There are myriad issues that impede researchers from openly, and most importantly, rapidly sharing data, including lack of incentives: no credit, limited funding benefits, and little impact on career advancement; and cultural issues: the fear of being scooped. However, scientific publishers —the communicators of science and a key mechanism by which a researcher’s productivity is measured— can, and should, play a central role in promoting data sharing. Data citation and publication are just some of the ways we can support and encourage researchers who share data. Here, I will provide examples to help make clear the need for publishers to play an active role in this process and provide potential ways to facilitate our ability to promote open and rapid data sharing. This is not easy; but it is essential.
4. Original Bioinformatics Definition
• It seemed to us that one of the defining
properties of life was information processing
in its various forms, e.g., information
accumulation during evolution, information
transmission from DNA to intra- and
intercellular processes, and the interpretation
of such information at multiple levels.
Hogeweg, P. The Roots of Bioinformatics in Theoretical Biology. PLoS Comput Bio. 2011.
5. National Center for Biotechnology
Information (NCBI)
• Bioinformatics
– Bioinformatics is the field of science in which
biology, computer science, and information
technology merge to form a single discipline.
• Computational Biology
– The actual process of analyzing and interpreting
data is referred to as computational biology.
6. Why Do We Need Bioinformatics?
http://www.philcallaway.ab.ca/images/Cartoons/privacy%20cartoon2.jpg
13. Bioinformatics in the News
• A New Bioinformatics System Improves Medical Diagnosis
– http://www.sciencedaily.com/releases/2011/06/110628094833.
htm
• Pacific Biosciences Contributes Whole Genome Sequence
Data for German E. Coli Outbreak Strain and 11 Related
Strains for Comparative Analysis
– http://www.marketwatch.com/story/pacific-biosciences-
contributes-whole-genome-sequence-data-for-german-e-coli-
outbreak-strain-and-11-related-strains-for-comparative-analysis-
2011-07-06?reflink=MW_news_stmp
• Initiative Launched to Sequence 5,000 Insects
– http://www.genomeweb.com/sequencing/initiative-launched-
sequence-5000-insects
14. Preparing for a Career in
Bioinformatics
• Try a whole bunch of stuff!
• Don’t give up on math
• Learn/understand Computer Science
• Don’t forget, the biology is what people care
about
http://www.youtube.com/watch?v=kZ3y8e676cw&feature=related
15. Where Can You Work In
Bioinformatics?
http://www.tomhcanderson.com/wp-content/uploads/2010/11/textminingacademia.jpg
http://www.freefoto.com/images/13/53/13_53_21---Sunset--Teesside-Industry_web.jpg
http://www.youtube.com/watch?v=ydXLP3MlO58
http://www.youtube.com/watch?v=dJrpSvsFXFI
16. Gene Patenting
http://www.cbsnews.com/video/watch/?id=6362525n
•Requirements for a patent
•Novelty, Usefulness, and Nonobvious
•Dr. Picard, through an intense genomic analysis of many patients, has
recently isolated a gene from humans that is responsible for providing
immunity to HIV. Recognizing the obvious therapeutic benefits this gene
might hold, he files a patent request with the US patent office.
•Should Dr. Picard’s patent be accepted?
•If Dr. Picard’s patent is accepted, what should other researchers and
companies be allowed to do with his gene (i.e., what kinds of research
and products can they develop)?
•What are the pros and cons of allowing Dr. Picard to patent his
discovery?
18. Central Dogma of Biology
http://library.thinkquest.org/C0122429/pictures/centraldogma2.gif
The central dogma of molecular biology deals with the detailed residue-
by-residue transfer of sequential information. It states that information
cannot be transferred back from protein to either protein or nucleic acid.
Crick F (August 1970). "Central dogma of molecular biology.". Nature 227 (5258): 561–3.
20. The Case for DNA
http://www.visionlearning.com/library/modules/mid149/Image/VLObject-3756-080922120939.jpg
21. The Structure of DNA
Experiment: Watson J.D. and Crick F.H.C. (1953). "A Structure for Deoxyribose Nucleic
Acid" (PDF). Nature 171 (4356): 737–738.
Image: http://shs.westport.k12.ct.us/forensics/10-dna/dna_molecule.gif