Parameterized maximum entropy models predict variability of metabolic scaling across tree communities and populations

Ecology ◽  
2020 ◽  
Vol 101 (6) ◽  
Author(s):  
Meng Xu
Keyword(s):  
Maximum Entropy ◽  
Metabolic Scaling ◽  
Maximum Entropy Models ◽  
Tree Communities

Identifying Semantic Roles Using Maximum Entropy Models

2004 ◽  
pp. 163-170 ◽  
Author(s):  
Paloma Moreda ◽  
Manuel Fernández ◽  
Manuel Palomar ◽  
Armando Suárez
Keyword(s):  
Maximum Entropy ◽  
Semantic Roles ◽  
Maximum Entropy Models

scholarly journals MPF–BML: a standalone GUI-based package for maximum entropy model inference

2019 ◽  
Vol 36 (7) ◽  
pp. 2278-2279
Author(s):  
Ahmed A Quadeer ◽  
Matthew R McKay ◽  
John P Barton ◽  
Raymond H Y Louie
Keyword(s):  
Maximum Entropy ◽  
Fitness Landscape ◽  
Sequence Data ◽  
Surface Proteins ◽  
Supplementary Information ◽  
Model Parameters ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Widespread Application ◽  
Maximum Entropy Models

Abstract Summary Learning underlying correlation patterns in data is a central problem across scientific fields. Maximum entropy models present an important class of statistical approaches for addressing this problem. However, accurately and efficiently inferring model parameters are a major challenge, particularly for modern high-dimensional applications such as in biology, for which the number of parameters is enormous. Previously, we developed a statistical method, minimum probability flow–Boltzmann Machine Learning (MPF–BML), for performing fast and accurate inference of maximum entropy model parameters, which was applied to genetic sequence data to estimate the fitness landscape for the surface proteins of human immunodeficiency virus and hepatitis C virus. To facilitate seamless use of MPF–BML and encourage more widespread application to data in diverse fields, we present a standalone cross-platform package of MPF–BML which features an easy-to-use graphical user interface. The package only requires the input data (protein sequence data or data of multiple configurations of a complex system with large number of variables) and returns the maximum entropy model parameters. Availability and implementation The MPF–BML software is publicly available under the MIT License at https://github.com/ahmedaq/MPF-BML-GUI. Supplementary information Supplementary data are available at Bioinformatics online.

Maximum-entropy models of galaxies

1988 ◽  
Vol 327 ◽  
pp. 82 ◽  
Author(s):  
Douglas O. Richstone ◽  
Scott Tremaine
Keyword(s):  
Maximum Entropy ◽  
Maximum Entropy Models
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