Table1_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX by Zhen Wang (72451)

“…Weighted gene coexpression network analysis (WGCNA) and two machine learning algorithms were employed to identify potential biomarkers for CRPC. …”

MSVM-RFE algorithm for screening key genes. by Ya xi Zhu (11624730)

Table 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.xlsx by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Image 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Image 4_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Image 5_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Image 3_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Image 2_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…These genes were strongly associated with the infiltration of both innate and adaptive immune cells, as well as immune pathways. …”

Rare variants in <i>SMYD1</i> and <i>BMP10</i> identified in family 346 are functionally damaging. by David M. Gordon (3259002)

Subjects:

Performance of ENQUIRE’s gene normalization algorithm. by Luca Musella (19986312)

Probably pathogenic variants (algorithms). by Felipe Fidalgo (642532)

Available functions in the phase-shifting package. by Raul Castañeda (13932971)

Available functions in the numerical propagation package. by Raul Castañeda (13932971)

Available functions in the phase reconstruction package. by Raul Castañeda (13932971)

Synthesized construct and experimental design. by Antoine L. Decrulle (11540003)

Subjects:

Comparison of results of different algorithms. by Zhongzhong Guo (12133402)

Subjects: “…differentially expressed genes…”

Algorithmic assessment reveals functional implications of GABRD gene variants linked to idiopathic generalized epilepsy by Ayla Arslan (17943365)

“…</p> <p>The study employs a combination of in silico algorithms to analyze 82 variants of unknown clinical significance of GABRD gene sourced from the ClinVar database. …”

The eVIP algorithm uses RNA-seq data to predict the function of somatic mutations. by Alexis M. Thornton (11068403)

Subjects:

Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

Table 6_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”