Journal: The Journal of International Medical Research

Article Title: Screening of genes characteristic of pancreatic cancer by LASSO regression combined with support vector machine and recursive feature elimination, and immune correlation analysis

doi: 10.1177/03000605241233160

Figure Lengend Snippet: (a) LASSO regression screening for genes characteristic of pancreatic cancer. The point with the smallest cross validation error is 13, representing a total of 13 genes. (b) SVM–RFE screening for genes characteristic of pancreatic cancer. The point with the smallest cross-validation error is 19, representing a total of 19 genes and (c) Venn diagram of the intersection of the characteristic genes of pancreatic cancer screened by two machine learning methods. LASSO, least absolute shrinkage and selection operator; SVM–RFE, support vector machine and recursive feature elimination.

Article Snippet: The characteristic genes identified both by LASSO regression and SVM–RFE were analyzed by intersection analysis using the “venn” package in R studio software to identify intersection genes.

Techniques: Biomarker Discovery, Selection, Plasmid Preparation

Journal: PeerJ

Article Title: eDNA metabarcoding shows highly diverse but distinct shallow, mid-water, and deep-water eukaryotic communities within a marine biodiversity hotspot

doi: 10.7717/peerj.19249

Figure Lengend Snippet: Venn diagram representing the number of exclusive and shared OTUs found in shallow and deep (mid-water and deep-water) samples (A), and the presence of exclusive and shared identified taxonomic classes (B).

Article Snippet: Histograms to explore the distribution of OTUs per sample were created with the ggplot2 package and Venn Diagrams with the Venn Diagram package in R ( ) and RStudio v2022.02.0 ( ).

Techniques: