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LiquidBrain Bioinformatics offers a concise guide to 16s rRNA sequencing analysis and visualization, covering OTU identification, phylotype analysis, and diversity measures in under an hour.
Learn to analyze cancer somatic mutations using MAFtools R package with LiquidBrain Bioinformatics. Understand mutation types and their impact on patient survival in under an hour.
Learn data imputation techniques in R with LiquidBrain Bioinformatics. Understand different methods, use the mice package, and evaluate algorithm performance in under an hour.
Learn to identify TCGA biomarkers using basic machine learning with LiquidBrain Bioinformatics. This under 1-hour program covers data normalization, PCA analysis, neural network construction, and more.
Learn to integrate and compare gene expression datasets from different conditions with LiquidBrain Bioinformatics. Less than 1-hour workload.
Learn statistical modeling and linear mixed model application in R with LiquidBrain Bioinformatics. Understand relationships between variables and prevent false correlations.
Learn to combine multiple heatmaps using ComplexHeatmap in less than an hour with LiquidBrain Bioinformatics. Master dataset creation, plot identification, and annotation.
Learn to create intricate heatmaps in bioinformatics research with LiquidBrain Bioinformatics. Master the use of the ComplexHeatmap package in under an hour.
Understand the use of log2FC and workings of DESeq2 in less than an hour with LiquidBrain Bioinformatics. Ideal for those interested in differential expression analysis.
LiquidBrain Bioinformatics offers a concise tutorial on ScRNA-Seq clustering and marker identification using the Seurat package, with a focus on data import, QC, normalization, and visualization.
Learn to isolate Differential Expressed Genes (DEGs) from FastQ using open-source tools with LiquidBrain Bioinformatics. This under-1-hour material covers Rsubread, DeSEQ2, and data analysis.
Learn to predict disease progression using Survival Analysis on cancer data with RStudio, offered by LiquidBrain Bioinformatics. Less than 1-hour workload.
Explore the intersection of deep learning and bioinformatics with LiquidBrain Bioinformatics. Learn about BTINET, Auto Encoder, and Deep Belief Network in under an hour.
Learn to run basic statistical analysis using R with LiquidBrain Bioinformatics. This less than 1-hour material covers data import, correlation, linear models, and more.
Learn to automate tasks in Google Suite with App Scripts, including report generation from raw CDC EU data, in under an hour with LiquidBrain Bioinformatics.
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