A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

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

Lagrange-NG: The next generation of Lagrange. | LitMetric

Lagrange-NG: The next generation of Lagrange.

Syst Biol

Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany.

Published: May 2023

AI Article Synopsis

  • The DEC model of biogeography is computationally intensive, requiring significant processing time for large datasets, limiting analyses based on the number of regions.
  • The newly developed tool, Lagrange-NG, offers up to 49 times faster performance with multithreading and 26 times faster with a single thread, enabling efficient analysis of up to 12 regions in about 18 minutes.
  • Lagrange-NG not only improves computational speed by using Krylov subspaces for matrix exponential calculations, but also adheres to higher coding quality standards, making it a reliable and accessible tool for researchers under GPL2.

Article Abstract

Computing ancestral ranges via the Dispersion Extinction and Cladogensis (DEC) model of biogeography is characterized by an exponential number of states relative to the number of regions considered. This is because the DEC model requires computing a large matrix exponential, which typically accounts for up to 80% of overall runtime. Therefore, the kinds of biogeographical analyses that can be conducted under the DEC model are limited by the number of regions under consideration. In this work, we present a completely redesigned efficient version of the popular tool Lagrange which is up to 49 times faster with multithreading enabled, and is also 26 times faster when using only one thread. We call this new version Lagrange-NG (Lagrange-Next Generation). The increased computational efficiency allows Lagrange-NG to analyze datasets with a large number of regions in a reasonable amount of time, up to 12 regions in approximately 18 min. We achieve these speedups using a relatively new method of computing the matrix exponential based on Krylov subspaces. In order to validate the correctness of Lagrange-NG, we also introduce a novel metric on range distributions for trees so that researchers can assess the difference between any two range inferences. Finally, Lagrange-NG exhibits substantially higher adherence to coding quality standards. It improves a respective software quality indicator as implemented in the SoftWipe tool from average (5.5; Lagrange) to high (7.8; Lagrange-NG). Lagrange-NG is freely available under GPL2. [Biogeography; Phylogenetics; DEC Model.].

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10198646PMC
http://dx.doi.org/10.1093/sysbio/syad002DOI Listing

Publication Analysis

Top Keywords

dec model
12
number regions
12
matrix exponential
8
times faster
8
lagrange-ng
7
lagrange-ng generation
4
generation lagrange
4
lagrange computing
4
computing ancestral
4
ancestral ranges
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!