Genotype to phenotype prediction using transcriptomics and proteomics data.
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Updated
Jan 7, 2022 - R
Genotype to phenotype prediction using transcriptomics and proteomics data.
Computational biology functions I made to help in my analyses.
Deep learning model to predict chemotherapeutic sensitivity based on transcriptomic data.
R scripts used to analyze single-nucleus RNA-seq data generated from in vitro differentiated pancreatic organoids, described in Huang, L. et al. 2021 (in press).
Analysis of summer nurse & forager and winter honey bee fat body and flight muscle transcriptomes
Ensemble of convolutional neural networks for transcriptional classification
RNAseq pipeline for Pasini's lab written in snakemake
Reproducible scripts for (P. Carella et al) manuscript
Bioinformatic data mining pipeline used in my college research project. https://www.mdpi.com/2223-7747/10/8/1647/htm#
LaTeX sources for my PhD thesis RNA Sequencing for Molecular Diagnostics in Breast Cancer at the Lund University Faculty of Medicine (published December 2020).
Graphical User Interface using Shiny for RNA-seq analysis
Re-analysis of RNA seq data from Andrade et al
How to run transcriptome analysis on SAGA
Explore spatial organization of a mouse brain coronal section with Scanpy and Squidpy in this GitHub repository. Analyze cell interactions, visualize distributions, and uncover patterns using various data exploration and spatial analysis techniques.
Expectation-Maximization-based clustering algorithm to identify groups defined by biological variates as clusters in single-cell transcriptomic data.
R scripts for human and marine data analysis
Data and code used in the Plant Genomes dashboard
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