Effect of different randomization constraints on pattern detection.

<p>Example of how applying different constraints to matrix randomization can lead to contrasting resulst in pattern detection. In this example, we apply the same pattern detection workflow as described in <a href="https://journals.plos.org/complexsystems//article/info:doi/10.1371/journ...

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Bibliographic Details
Main Author:	Zachary P. Neal (9946331) (author)
Other Authors:	Annabell Cadieux (19797668) (author), Diego Garlaschelli (735361) (author), Nicholas J. Gotelli (7159646) (author), Fabio Saracco (823184) (author), Tiziano Squartini (735359) (author), Shade T. Shutters (11133439) (author), Werner Ulrich (623723) (author), Guanyang Wang (19797671) (author), Giovanni Strona (117060) (author)
Published:	2024
Subjects:	Cell Biology Biotechnology Evolutionary Biology Developmental Biology Cancer Mathematical Sciences not elsewhere classified projected onto pairs many research fields examples include ecology broad scientific audience briefly reviewing examples different technical domains randomizing certain elements null &# 8217 methods </ p common data structure use different terminology matrices representing binary original data null models different backgrounds &# 8216 common need common language translating concepts structural constraints specific techniques reference point randomized matrices preserving row pattern detection original matrix nevertheless promoted network metrics methodological developments matrices created major approaches independent development equivalently expressed empirical matrix diversity statistics distinct entities different disciplines conceptual importance computational challenges benchmark ensemble
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Effect of different randomization constraints on pattern detection.

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