Automatic cropping algorithm. by Thomas W Georgi (12427189)

Prediction performance of different optimization algorithms. by Ali-Kemal Aydin (10968731)

“…<p>(A) 3 algorithms were compared in terms of the residuals of the cost function of the optimized TF on 7 mice datasets (Derivative free algorithm failed in optimizing a TF in a mouse). …”

Convergence graphs of the ten algorithms for the five functions from the CEC 2014 suite. by Juan Yao (293170)

Original data for the study "<b>Improving basin-wide flood estimation from a global hydrological model through spatiotemporal-pattern-</b><b>based </b><b>machine learning</b>" by Jiaqing Wang (18814630)

The benchmark functions. by Shuhui Yu (1535500)

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”

HIV exposure risk algorithm. HIV exposure risk algorithm based on available data from the Tonse Padmozi trial. by Anna M. Leone (22486372)

<b>Gene Catalog and Associated Functional Data</b> for BioProject PRJNA1311452 by Satheeswaran Thangaraj (22187269)

Screening and diagnosis pipeline for the Challenge. by Matthew A. Reyna (16965038)

Subjects:

Application of the algorithm to unseen data. Presynaptic neurons labelled by rabies viral injection into layer 2/3 primary visual cortex in Penk-Cre mice. by Adam L. Tyson (10892822)

Skeletonisation algorithm. by Jordan Hembrow (16908051)

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

“…<p>(A), (B) Algorithm performance, evaluated over 50 simulated datasets generated as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012590#pcbi.1012590.g001" target="_blank">Fig 1</a> with <i>N</i> = 3 true groups, 900 samples and 10% simulated measurement noise. …”

Visual depiction of the MSA algorithm. by Kayson Fakhar (12890364)

Functional validation of the metastasis-predictive genes inferred by PLUS from TCGA data. by Junyi Zhou (495644)

GELU function. by Yuanzhou Zheng (15195249)

Flowchart of one iteration of the CE-Symm algorithm. by Spencer E. Bliven (6672755)

As for Fig 2, we present failure rates as a function of the cohort size (vertical axis) versus the number of distractors (horizontal axis), for the Smyth and McClave baseline algorithm from [76]. by Daniela Huppenkothen (9174507)

Conservation and functional variation across TcdB subtypes. by Michael J. Mansfield (9922934)

Algorithm detection steps. by José M. Rivera-Arbeláez (12418512)

Flowchart of the general algorithm for one trial. by Junying Wang (509009)