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)

Subjects:

A parabolic relationship between prediction errors and learning rates obtained by a cubic learning algorithm. by Boluwatife Ikwunne (22238697)

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

Subjects:

Immune infiltration analysis by CIBERSORT algorithm. by Lanying Shen (22755930)

Immune infiltration analysis by CIBERSORT algorithm. by Lanying Shen (22755930)

IDEN algorithm and gene pair-based drug repurposing. by Yao Jiang (1469614)

The algorithm for the same-day surgery protocol. by Magnus Tveit (11442200)

Effect of “nonfunctional group” on function. by Yuanchen Zhao (12905580)

Subjects:

Output groupings of the 3 algorithms for a linear degradation chain of <i>N</i> = 3 metabolites. by Yuanchen Zhao (12905580)

Subjects:

Iteration versus fitness function. by B. Venkatesh (17202747)

Model construction and validation (A) Construction of the model based on multiple machine learning algorithms. by Chengting Wu (21485612)

BNA Neuromarker scores as a function of LEDD. by Sharon Hassin-Baer (420354)

Subjects:

Overall accuracy of the neural network for the identification of high-risk COVID-19 patients, at the first clinical stage, as a function of (a) the number of neurons in the hidden... by Mario A. Quiroz-Juárez (11457140)

Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined. by Yuanchen Zhao (12905580)

Subjects:

Core genes were selected through PPI analysis based on three algorithms. by Dong-Hee Han (140305)

“…<p>Among 46 DEGs whose expression significantly changed in A549 and BEAS-2B cell lines, the core genes were selected using three algorithms: MCC, MNC, and DEGREE. …”

Distinct microbial and functional composition between age groups. by Elio L. Herzog (11576876)

Subjects: “…applying independent algorithms…”

A framework for improving localisation prediction algorithms. by Sven B. Gould (12237287)

“…Classifiers on which the algorithms are trained could include parameters such as the evolutionary distance of a species, non-coding regions, or a protein’s abundance as a currently neglected factor. …”

(a) Radar chart of these algorithms (23 Benchmark functions), (b) The sorting diagram of these algorithms (23 Benchmark functions). by Yu Liu (6938)

“…<p>(a) Radar chart of these algorithms (23 Benchmark functions), (b) The sorting diagram of these algorithms (23 Benchmark functions).…”

<b>Inappropriate application of mapping algorithms results in length-dependent gene abundances in metagenomic analysis</b> by Wenkai Teng (17150785)

Illustration of final objective function values consistency and possible objective function landscapes. by Fabian Fröhlich (848026)