Difference between revisions of "Bioinformatics"
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| − | [http://www.youtube.com/results?search_query=CRISPR | + | [http://www.youtube.com/results?search_query=Bioinformatics+Bioinformatics+genetics+CRISPR+gene+dna+artificial+intelligence+deep+learning Youtube search...] |
| − | [http://www.google.com/search?q= | + | [http://www.google.com/search?q=Bioinformatics+genetics+genomics+gene+dna+deep+machine+learning+ML ...Google search] |
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* [http://www.nature.com/articles/d41586-018-07225-z Machine learning spots natural selection at work in human genome | Amy Maxmen] | * [http://www.nature.com/articles/d41586-018-07225-z Machine learning spots natural selection at work in human genome | Amy Maxmen] | ||
* [http://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html DeepVariant: Highly Accurate Genomes With Deep Neural Networks | Mark DePristo and Ryan Poplin, Google Brain Team] | * [http://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html DeepVariant: Highly Accurate Genomes With Deep Neural Networks | Mark DePristo and Ryan Poplin, Google Brain Team] | ||
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| + | an interdisciplinary field that develops methods and software tools for understanding biological data, in particular when the data sets are large and complex. As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data. Bioinformatics has been used for in silico analyses of biological queries using mathematical and statistical techniques. | ||
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| + | Bioinformatics includes biological studies that use computer programming as part of their methodology, as well as a specific analysis "pipelines" that are repeatedly used, particularly in the field of genomics. Common uses of bioinformatics include the identification of candidates genes and single nucleotide polymorphisms (SNPs). Often, such identification is made with the aim of better understanding the genetic basis of disease, unique adaptations, desirable properties (esp. in agricultural species), or differences between populations. In a less formal way, bioinformatics also tries to understand the organisational principles within nucleic acid and protein sequences, called proteomics. [http://en.wikipedia.org/wiki/Bioinformatics Wikipedia] | ||
<youtube>s6rJLXq1Re0</youtube> | <youtube>s6rJLXq1Re0</youtube> | ||
Revision as of 09:45, 14 June 2020
Youtube search... ...Google search
- Case Studies
- COVID-19
- DIY Human CRISPR Guide | The Odin
- Machine learning spots natural selection at work in human genome | Amy Maxmen
- DeepVariant: Highly Accurate Genomes With Deep Neural Networks | Mark DePristo and Ryan Poplin, Google Brain Team
an interdisciplinary field that develops methods and software tools for understanding biological data, in particular when the data sets are large and complex. As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data. Bioinformatics has been used for in silico analyses of biological queries using mathematical and statistical techniques.
Bioinformatics includes biological studies that use computer programming as part of their methodology, as well as a specific analysis "pipelines" that are repeatedly used, particularly in the field of genomics. Common uses of bioinformatics include the identification of candidates genes and single nucleotide polymorphisms (SNPs). Often, such identification is made with the aim of better understanding the genetic basis of disease, unique adaptations, desirable properties (esp. in agricultural species), or differences between populations. In a less formal way, bioinformatics also tries to understand the organisational principles within nucleic acid and protein sequences, called proteomics. Wikipedia
CRISPR
CRISPR Kit
CRISPR Explained
What Came First, Cells or Viruses?
Youtube search... ...Google search
- Markov Model (Chain, Discrete Time, Continuous Time, Hidden)
- Phylogenetic Hidden Markov Models | Adam Siepel and David Haussler
- Phylogeny Programs | Joe Felsenstein - University of Washington Here are 392 phylogeny packages and 54 free web servers ... PHYLIP (the PHYLogeny Inference Package) Methods that are available in the package include parsimony, distance matrix, and likelihood methods, including bootstrapping and consensus trees. Data types that can be handled include molecular sequences, gene frequencies, restriction sites and fragments, distance matrices, and discrete characters.
