Journal Article

FZJ-2020-04154

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png HOPS: high-performance library for (non-)uniform sampling of convex-constrained models

Jadebeck, J. F.FZJ* ; Theorell, A.FZJ* ; Leweke, S.FZJ* ; Nöh, K. (Corresponding author)FZJ*

2020
Oxford Univ. Press Oxford

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Please use a persistent id in citations: doi:10.1093/bioinformatics/btaa872

Abstract: The C++ library Highly Optimized Polytope Sampling (HOPS) provides implementations of efficient and scalable algorithms for sampling convex-constrained models that are equipped with arbitrary target functions. For uniform sampling, substantial performance gains were achieved compared to the state-of-the-art. The ease of integration and utility of non-uniform sampling is showcased in a Bayesian inference setting, demonstrating how HOPS interoperates with third-party software.

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Contributing Institute(s):

1. Biotechnologie (IBG-1)

Research Program(s):

1. 583 - Innovative Synergisms (POF3-583) (POF3-583)

Appears in the scientific report 2021

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Database coverage:
; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; PubMed Central ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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