Functional effect prediction of FUS mutations by ten nsSNP prediction algorithms. by L. F. S. Bonet (11502082)

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:

Heat maps of mean scores over 50 datasets of the algorithms as a function of relative noise and number of samples. by Yuanchen Zhao (12905580)

Subjects:

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

Subjects:

Flowchart of system algorithm. by Syed Zahurul Islam (9635163)

Coarse-fine optimization algorithm. by Chao Ma (207385)

“…The improved gradient extraction method combines the Scale Invariant Feature Transformation (SIFT) algorithm to form a new multi-scale image sharpness evaluation function, SIFT Quad-Tenen. …”

Types of training algorithms. by Caixia Yan (6647072)

Artificial colony algorithm flow. by Jianpeng Zhang (528185)

Subjects:

Pseudo-code of ABC algorithm. by Jianpeng Zhang (528185)

Subjects:

Parameters of the test function. by Yiqiong Gao (16698968)

“…The adaptive adjustment of the transition probability effectively balances the development and exploration abilities of the algorithm. The improved flower pollination algorithm (IFPA) outperformed six classical benchmark functions that were used to verify the superiority of the improved algorithm. …”

Flowchart of step() function. by Raed Alharthi (18340157)

On-Demand Optimization of Colorimetric Gas Sensors Using a Knowledge-Aware Algorithm-Driven Robotic Experimental Platform by Zhehong Ai (17937324)

Subjects: “…customized multiobjective functions…”

Radius of gyration (RG) of the backbone atoms of the protein as a function of time. by L. F. S. Bonet (11502082)

Solvent-accessible surface area (SASA) of the protein as a function of time. by L. F. S. Bonet (11502082)

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

Subjects:

Summary of results of naïve Bayes algorithms. by Christopher E. Niemczak (8586861)

Subjects:

The iteration curve of the test function. by Jian Kong (164512)

“…Then the optimization parameters and scope were determined, and multi-objective optimization and direction preference algorithms were introduced. A chaotic optical performance optimization model based on improved multi-objective genetic algorithm was constructed using adaptive functions as evaluation indicators. …”

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:

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

Subjects:

Root mean square deviation (RMSD) of the backbone atoms of the protein as a function of time. by L. F. S. Bonet (11502082)