"Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA." - Information and Links:

Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA. - Info and Reading Options

"Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA." and the language of the book is English.


“Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.” Metadata:

  • Title: ➤  Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.
  • Authors:
  • Language: English

Edition Identifiers:

  • Internet Archive ID: pubmed-PMC4006459

AI-generated Review of “Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.”:


"Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA." Description:

The Internet Archive:

This article is from <a href="//archive.org/search.php?query=journaltitle%3A%28BMC%20Systems%20Biology%29" rel="ugc nofollow">BMC Systems Biology</a>, <a href="//archive.org/search.php?query=journaltitle%3A%28BMC%20Systems%20Biology%29%20AND%20volume%3A%288%29" rel="ugc nofollow">volume 8</a>.<h2>Abstract</h2>Background: Genome-wide time-series data provide a rich set of information for discovering gene regulatory relationships. As genome-wide data for mammalian systems are being generated, it is critical to develop network inference methods that can handle tens of thousands of genes efficiently, provide a systematic framework for the integration of multiple data sources, and yield robust, accurate and compact gene-to-gene relationships. Results: We developed and applied ScanBMA, a Bayesian inference method that incorporates external information to improve the accuracy of the inferred network. In particular, we developed a new strategy to efficiently search the model space, applied data transformations to reduce the effect of spurious relationships, and adopted the g-prior to guide the search for candidate regulators. Our method is highly computationally efficient, thus addressing the scalability issue with network inference. The method is implemented as the ScanBMA function in the networkBMA Bioconductor software package. Conclusions: We compared ScanBMA to other popular methods using time series yeast data as well as time-series simulated data from the DREAM competition. We found that ScanBMA produced more compact networks with a greater proportion of true positives than the competing methods. Specifically, ScanBMA generally produced more favorable areas under the Receiver-Operating Characteristic and Precision-Recall curves than other regression-based methods and mutual-information based methods. In addition, ScanBMA is competitive with other network inference methods in terms of running time.

Read “Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.”:

Read “Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.” by choosing from the options below.

Available Downloads for “Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.”:

"Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA." is available for download from The Internet Archive in "texts" format, the size of the file-s is: 21.02 Mbs, and the file-s went public at Wed Oct 22 2014.

Legal and Safety Notes

Copyright Disclaimer and Liability Limitation:

A. Automated Content Display
The creation of this page is fully automated. All data, including text, images, and links, is displayed exactly as received from its original source, without any modification, alteration, or verification. We do not claim ownership of, nor assume any responsibility for, the accuracy or legality of this content.

B. Liability Disclaimer for External Content
The files provided below are solely the responsibility of their respective originators. We disclaim any and all liability, whether direct or indirect, for the content, accuracy, legality, or any other aspect of these files. By using this website, you acknowledge that we have no control over, nor endorse, the content hosted by external sources.

C. Inquiries and Disputes
For any inquiries, concerns, or issues related to the content displayed, including potential copyright claims, please contact the original source or provider of the files directly. We are not responsible for resolving any content-related disputes or claims of intellectual property infringement.

D. No Copyright Ownership
We do not claim ownership of any intellectual property contained in the files or data displayed on this website. All copyrights, trademarks, and other intellectual property rights remain the sole property of their respective owners. If you believe that content displayed on this website infringes upon your intellectual property rights, please contact the original content provider directly.

E. Fair Use Notice
Some content displayed on this website may fall under the "fair use" provisions of copyright law for purposes such as commentary, criticism, news reporting, research, or educational purposes. If you believe any content violates fair use guidelines, please reach out directly to the original source of the content for resolution.

Virus Scanning for Your Peace of Mind:

The files provided below have already been scanned for viruses by their original source. However, if you’d like to double-check before downloading, you can easily scan them yourself using the following steps:

How to scan a direct download link for viruses:

  • 1- Copy the direct link to the file you want to download (don’t open it yet).
    • (a free online tool) and paste the direct link into the provided field to start the scan.
  • 2- Visit VirusTotal (a free online tool) and paste the direct link into the provided field to start the scan.
  • 3- VirusTotal will scan the file using multiple antivirus vendors to detect any potential threats.
  • 4- Once the scan confirms the file is safe, you can proceed to download it with confidence and enjoy your content.

Available Downloads

  • Source: Internet Archive
  • Internet Archive Link: Archive.org page
  • All Files are Available: Yes
  • Number of Files: 14
  • Number of Available Files: 14
  • Added Date: 2014-10-22 18:13:38
  • Scanner: Internet Archive Python library 0.7.2
  • PPI (Pixels Per Inch): 600
  • OCR: ABBYY FineReader 9.0

Available Files:

1- Text PDF

  • File origin: original
  • File Format: Text PDF
  • File Size: 0.00 Mbs
  • File Name: PMC4006459-1752-0509-8-47.pdf
  • Direct Link: Click here

2- Item Tile

  • File origin: original
  • File Format: Item Tile
  • File Size: 0.00 Mbs
  • File Name: __ia_thumb.jpg
  • Direct Link: Click here

3- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC4006459_files.xml
  • Direct Link: Click here

4- JSON

  • File origin: original
  • File Format: JSON
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC4006459_medline.json
  • Direct Link: Click here

5- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC4006459_meta.sqlite
  • Direct Link: Click here

6- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC4006459_meta.xml
  • Direct Link: Click here

7- DjVu

  • File origin: derivative
  • File Format: DjVu
  • File Size: 0.00 Mbs
  • File Name: PMC4006459-1752-0509-8-47.djvu
  • Direct Link: Click here

8- Animated GIF

  • File origin: derivative
  • File Format: Animated GIF
  • File Size: 0.00 Mbs
  • File Name: PMC4006459-1752-0509-8-47.gif
  • Direct Link: Click here

9- Abbyy GZ

  • File origin: derivative
  • File Format: Abbyy GZ
  • File Size: 0.00 Mbs
  • File Name: PMC4006459-1752-0509-8-47_abbyy.gz
  • Direct Link: Click here

10- DjVuTXT

  • File origin: derivative
  • File Format: DjVuTXT
  • File Size: 0.00 Mbs
  • File Name: PMC4006459-1752-0509-8-47_djvu.txt
  • Direct Link: Click here

11- Djvu XML

  • File origin: derivative
  • File Format: Djvu XML
  • File Size: 0.00 Mbs
  • File Name: PMC4006459-1752-0509-8-47_djvu.xml
  • Direct Link: Click here

12- Single Page Processed JP2 ZIP

  • File origin: derivative
  • File Format: Single Page Processed JP2 ZIP
  • File Size: 0.02 Mbs
  • File Name: PMC4006459-1752-0509-8-47_jp2.zip
  • Direct Link: Click here

13- Scandata

  • File origin: derivative
  • File Format: Scandata
  • File Size: 0.00 Mbs
  • File Name: PMC4006459-1752-0509-8-47_scandata.xml
  • Direct Link: Click here

14- Archive BitTorrent

  • File origin: metadata
  • File Format: Archive BitTorrent
  • File Size: 0.00 Mbs
  • File Name: pubmed-PMC4006459_archive.torrent
  • Direct Link: Click here

Search for “Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.” downloads:

Visit our Downloads Search page to see if downloads are available.

Find “Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.” in Libraries Near You:

Read or borrow “Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.” from your local library.

Buy “Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.” online:

Shop for “Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA.” on popular online marketplaces.



Find "Fast Bayesian Inference For Gene Regulatory Networks Using ScanBMA." in Wikipdedia