Pipeline of the interactor algorithm. by Jose Cleydson F. Silva (8685594)

A) Ranking of models trained on different feature sets across all tested algorithms, sorted by their F1-score. by Jose Cleydson F. Silva (8685594)

Table3_Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.XLSX by Lei Chen (54296)

“…In this study, the protein–protein interaction network, functional annotation of proteins and a group of direct proteins with known subcellular localization were used to construct models. …”

Top-ranked hub genes identified by 5 cytoHubba algorithms. by Jun Li (6494)

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

The GOR4 and SOPMA algorithm findings. by Ahmad Abdullah Mahdeen (19704401)

Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

Genetic algorithms can be applied to higher-dimensional design problems. by Lu Hong (399882)

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Immune infiltration analysis by ssGSEA algorithm. by Yubin Xue (1537042)

(a-b) The LASSO algorithm was used for hyperparameter tuning and identification of the important predictive features. by Devi Soorya Narayana Sasikumar (22331743)

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GA[ESM,pMPNN,AF2Rank] algorithm flowchart. by Lu Hong (399882)

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Rosetta energy functions for membrane proteins cannot identify the inward-facing conformation of PfMATE. by Diego del Alamo (9925083)

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

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

Distribution of objective function values solved by three algorithms. by Meilin Zhu (688698)

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. …”

Dynamical comparison between Drosha and Dicer reveals functional motion similarities and dissimilarities by Rotem Aharoni (8108177)

“…Since dynamics is essential for protein function, a comparison at their dynamics level is fundamental for a complete understanding of the overall relations between these proteins. …”

Depiction of the theory, can sequence infer function? by Ashley I. Heinson (8124374)

PATH has state-of-the-art performance versus previous binding affinity prediction algorithms. by Yuxi Long (11024307)

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Mutations at functionally important interfaces. by Myo T. Naung (10873278)

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