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Bacteria Divide People Into 3 Types

Bacteria Divide People Into 3 Types. Article Source. Hosted on the New York Times Written by Carl Zimmer. Research Source. Article Posted on Nature. Research Authors:.

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Bacteria Divide People Into 3 Types

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  1. Bacteria Divide People Into 3 Types Article Source Hosted on the New York Times Written by Carl Zimmer Research Source Article Posted on Nature Research Authors: Manimozhiyan Arumugam, Jeroen Raes, Eric Pelletier, Denis Le Paslier, Takuji Yamada, Daniel R. Mende, Gabriel R. Fernandes, Julien Tap, Thomas Bruls, Jean-Michel Batto, Marcelo Bertalan, Natalia Borruel, Francesc Casellas, Leyden Fernandez, Laurent Gautier, Torben Hansen, Masahira Hattori, Tetsuya Hayashi, Michiel Kleerebezem, Ken Kurokawa, Marion Leclerc, Florence Levenez, Chaysavanh Manichanh, H. Bjørn Nielsen, Trine Nielsen, Nicolas Pons, Julie Poulain, Junjie Qin, Thomas Sicheritz-Ponten, Sebastian Tims, David Torrents, Edgardo Ugarte, Erwin G. Zoetendal, Jun Wang, Francisco Guarner, Oluf Pedersen, Willem M. de Vos, Søren Brunak, Joel Doré, MetaHIT Consortium (additional members), Jean Weissenbach, S. Dusko Ehrlich & Peer Bork

  2. Article Topic • Researchers looked at what bacteria is found in people's stomachs • Discovered people are host to one of three bacteria ecosystems • Discovery was made by analyzing the types of bacteria DNA found in test subjects’ skin and sweat • The DNA data was examined using clustering analysis

  3. Connection to Class ... The topic of the article does not relate directly to any material covered in class However It is interesting because it demonstrates using data to solve real world problems

  4. Background • Every Human is Host to 100 trillion bacteria • The researchers were looking for DNA related to 1,511 bacteria species • The researchers did not know what they were looking for: “We didn't have any hypothesis, Anything that came out would be new” -Dr. Bork

  5. Classification Analysis Trying to group things into known categories Examples: • Grouping donated blood by blood type • Looking for patients with low, med, and high risk for heart disease

  6. Clustering Analysis Looking for groups in data Clustering Analysis of Blood Groups By Percent of Population can Donate To/From AB A 100% B O Donate From 0% 0% 100% Donate To

  7. Clustering Analysis: Gut Microbes M Arumugam et al.Nature000, 1-7 (2011) doi:10.1038/nature09944

  8. Why Use Clustering Analysis • Clustering analysis highlights the existence of distinct groups in data • Can be used in a situation with a lot of data, but little knowledge of how to organize the data • It can provide enough information about a subject to allow more interesting questions to be asked

  9. Summary • Classification analysis is grouping data into known groups • Clustering analysis is looking for unknown groups in data • Clustering analysis is most useful when not much is known about a subject • Questions?

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