A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 143

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 143
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 209
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3098
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 574
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 488
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Attempt to read property "Count" on bool

Filename: helpers/my_audit_helper.php

Line Number: 3100

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3100
Function: _error_handler

File: /var/www/html/application/controllers/Detail.php
Line: 574
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 488
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Inference of differential gene regulatory networks using boosted differential trees. | LitMetric

AI Article Synopsis

  • - BoostDiff is a new method designed to detect changes in molecular networks linked to diseases by using an ensemble of differential regression trees, which helps in understanding complex regulatory interactions.
  • - It utilizes a novel approach called differential variance improvement to enhance network analysis, providing better insights into gene expression predictability and constructing differential networks.
  • - The method has shown superior performance over existing techniques in simulated data and has been effectively applied to real-world cases, including COVID-19 and various cancers, revealing important context-specific networks associated with disease pathways.

Article Abstract

Summary: Diseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections remains a challenging task and would benefit from the development of novel nonparametric approaches. We develop a new ensemble method called BoostDiff (boosted differential regression trees) to infer a differential network discriminating between two conditions. BoostDiff builds an adaptively boosted (AdaBoost) ensemble of differential trees with respect to a target condition. To build the differential trees, we propose differential variance improvement as a novel splitting criterion. Variable importance measures derived from the resulting models are used to reflect changes in gene expression predictability and to build the output differential networks. BoostDiff outperforms existing differential network methods on simulated data evaluated in four different complexity settings. We then demonstrate the power of our approach when applied to real transcriptomics data in COVID-19, Crohn's disease, breast cancer, prostate adenocarcinoma, and stress response in . BoostDiff identifies context-specific networks that are enriched with genes of known disease-relevant pathways and complements standard differential expression analyses.

Availability And Implementation: BoostDiff is available at https://github.com/scibiome/boostdiff_inference.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10948285PMC
http://dx.doi.org/10.1093/bioadv/vbae034DOI Listing

Publication Analysis

Top Keywords

differential trees
12
differential
9
boosted differential
8
changes regulatory
8
differential network
8
boostdiff
5
inference differential
4
differential gene
4
gene regulatory
4
regulatory networks
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!