IRIS-CC omics

IRIS-CC omics

Technologist for the Bioinformatics and Bioimaging Research Group of the IRIS-CC (UVic-UCC) - Ph.D. in Bioinformatics (UVic-UCC)

Iris-CC - Bioinformatics and Bioimaging (BI-SQUARED)

Tools

Welcome to the IRIS-CC Omics Tools Hub Your gateway to user-friendly tools and scripts for analyzing cutting-edge omics data. This platform is designed to make advanced bioinformatics accessible to everyone—from beginners to seasoned researchers—by providing intuitive guides and scripts for key areas of omics research.

Explore Our Tools: Transcriptomics: Dive into single-cell RNA-seq analysis with step-by-step tools for gene expression studies. Whether you’re new to RNA sequencing or looking for streamlined approaches, our scripts simplify complex workflows.

Multi-Omics Integration: Learn how to integrate and analyze diverse datasets (transcriptomics, proteomics, epigenomics) to uncover comprehensive biological insights. We offer practical solutions that unify different omics layers into cohesive analyses.

Machine Learning & Deep Learning: Harness the power of AI to analyze biological data with accessible, pre-built machine learning and deep learning models. Our tools allow you to implement predictive models without extensive coding knowledge.

Download my CV .

Interests
  • Computational Biology
  • Single Cell Omics

Tools

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IRIS-CC omics, 吳恩達
Dec 13, 2020 3 min read Demo, 教程
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Download the HTML Pre-Processing Seurat . R Markdown Primer de tot, carreguem les dades. Del SCC Squamos cell carcionma #setwd("C:/Users/Roger Casals/OneDrive/Escriptori/UOC ROGER/2n semestre/TFM/Final 5_5") setwd("C:/Users/Natàlia/Desktop/UOC ROGER/2n semestre/TFM/Primera prova") metadata2 <- data.
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Jul 12, 2019 6 min read
Writing technical content in Markdown
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IRIS-CC omics
Last updated on Sep 5, 2019 2 min read
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Projects

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All Deep Learning Other
Comparison of Single Cell trajectory inference methods in cancer immunotherapy
scRNA-seq complete analysis.
Code Follow
Comparison of Single Cell trajectory inference methods in cancer immunotherapy
Gene expression prediction under novel conditions using ATAC-seq-informed regulons
scRNA integration
Gene expression prediction under novel conditions using ATAC-seq-informed regulons
Machine learning and deep learning
Machine learning and deep learning methods to predict.
Code Follow
Machine learning and deep learning
Predicting gene expression on drug perturbations
An example of using the in-built project page.
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Predicting gene expression on drug perturbations

Recent Publications

Quickly discover relevant content by filtering publications.
IRIS-CC omics (2019). An example preprint / working paper.

PDF Code Dataset Poster Slides Video Source Document Custom Link

IRIS-CC omics, Robert Ford (2015). An example journal article. Journal of Source Themes, 1(1).

PDF Cite Code Slides

Example Talk
An example talk using Wowchemy’s Markdown slides feature.
Jun 1, 2030 1:00 PM — 3:00 PM Wowchemy HQ
Project Slides Follow
Example Talk

Contact

Feel free to reach out to me through the contact form below