Below 60 - Shop now
$44.20 with 20 percent savings
List Price: $54.99
FREE delivery May 12 - 15 to Nashville 37217. Order within 1 hr 51 mins. Details
Only 1 left in stock - order soon.
$$44.20 () Includes selected options. Includes initial monthly payment and selected options. Details
Price
Subtotal
$$44.20
Subtotal
Initial payment breakdown
Shipping cost, delivery date, and order total (including tax) shown at checkout.
Ships from
BOOKS_EXPRESS_USA
BOOKS_EXPRESS_USA
Ships from
BOOKS_EXPRESS_USA
Returns
30-day refund/replacement
30-day refund/replacement
This item can be returned in its original condition for a full refund or replacement within 30 days of receipt. You may receive a partial or no refund on used, damaged or materially different returns.
Read full return policy
Payment
Secure transaction
Your transaction is secure
We work hard to protect your security and privacy. Our payment security system encrypts your information during transmission. We don’t share your credit card details with third-party sellers, and we don’t sell your information to others. Learn more
Kindle app logo image

Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet, or computer - no Kindle device required.

Read instantly on your browser with Kindle for Web.

Using your mobile phone camera - scan the code below and download the Kindle app.

QR code to download the Kindle App

Machine Learning for Microbial Phenotype Prediction (BestMasters) 1st ed. 2016 Edition

by Roman Feldbauer (Author)
3.0 out of 5 stars 1 rating
{"desktop_buybox_group_1":[{"displayPrice":"$44.20","priceAmount":44.20,"currencySymbol":"$","integerValue":"44","decimalSeparator":".","fractionalValue":"20","symbolPosition":"left","hasSpace":false,"showFractionalPartIfEmpty":true,"offerListingId":"cA7aEZYYyhRYYE5iYbGO1JhbbxGNzSHrcfpGAhudX1jU2vpFb2ML3dYX0AQDfEPb715nWzZTo0xX58XwlEwG84gk2manx5OBPGijguZFsEzNvISPBnxidtp6qA8SpMBqlv8QcB06j%2FVHB6vD1NOgtNlGBZpUjsft3tVotSIZke4HCnYi9%2Bofow%3D%3D","locale":"en-US","buyingOptionType":"NEW","aapiBuyingOptionIndex":0}]}

Purchase options and add-ons

This thesis presents a scalable, generic methodology for microbial phenotype prediction based on supervised machine learning, several models for biological and ecological traits of high relevance, and the deployment in metagenomic datasets. The results suggest that the presented prediction tool can be used to automatically annotate phenotypes in near-complete microbial genome sequences, as generated in large numbers in current metagenomic studies. Unraveling relationships between a living organism's genetic information and its observable traits is a central biological problem. Phenotype prediction facilitated by machine learning techniques will be a major step forward to creating biological knowledge from big data.
Read more
Previous slide of product details
  1. ISBN-10
    9783658143183
  2. ISBN-13
    978-3658143183
  3. Edition
    1st ed. 2016
  4. Publication date
    June 24, 2016
  5. Part of series
    BestMasters
  6. Language
    English
  7. Dimensions
    5.83 x 0.28 x 8.27 inches
  8. Print length
    123 pages
Next slide of product details

Editorial Reviews

From the Back Cover

This thesis presents a scalable, generic methodology for microbial phenotype prediction based on supervised machine learning, several models for biological and ecological traits of high relevance, and the deployment in metagenomic datasets. The results suggest that the presented prediction tool can be used to automatically annotate phenotypes in near-complete microbial genome sequences, as generated in large numbers in current metagenomic studies. Unraveling relationships between a living organism's genetic information and its observable traits is a central biological problem. Phenotype prediction facilitated by machine learning techniques will be a major step forward to creating biological knowledge from big data.
Contents
  • Microbial Genotypes and Phenotypes
  • Basics of Machine Learning
  • Phenotype Prediction Packages
  • A Model for Intracellular Lifestyle
Target Groups
  • Teachers and students in the fields of bioinformatics, molecular biology and microbiology
  • Executives and specialists in the field of microbiology, computational biology and machine learning
About the AuthorRoman Feldbauer is currently employed at the Austrian Research Institute for Artificial Intelligence (OFAI) and PhD student at the University of Vienna. His research interests are machine learning, data science, bioinformatics, comparative genomics and neuroscience. In one of his current projects he investigates large biological databases in regard to the „curse of dimensionality“.

About the Author

Roman Feldbauer is currently employed at the Austrian Research Institute for Artificial Intelligence (OFAI) and PhD student at the University of Vienna. His research interests are machine learning, data science, bioinformatics, comparative genomics and neuroscience. In one of his current projects he investigates large biological databases in regard to the „curse of dimensionality“.

Product details

  • ASIN ‏ : ‎ 3658143185
  • Publisher ‏ : ‎ Springer Spektrum; 1st ed. 2016 edition (June 24, 2016)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 123 pages
  • ISBN-10 ‏ : ‎ 9783658143183
  • ISBN-13 ‏ : ‎ 978-3658143183
  • Item Weight ‏ : ‎ 5.7 ounces
  • Dimensions ‏ : ‎ 5.83 x 0.28 x 8.27 inches
  • Customer Reviews:
    3.0 out of 5 stars 1 rating

Customer reviews

3 out of 5 stars
1 global rating

Review this product

Share your thoughts with other customers
Write a customer review

No customer reviews

There are 0 customer reviews and 1 customer rating.