Pablo A Moreno

An integrated view of baseline protein expression in human tissues

The paper reanalyzes 24 public proteomics datasets to assess baseline protein abundance in 31 human organs and integrates the results into the Expression Atlas for combined proteomics and transcriptomics analysis.

Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues

The paper reanalyzes proteomics datasets from mouse and rat tissues to compare baseline protein expression across species and organs, finding high correlation among orthologs in brain, kidney, heart, and liver.

Implementing the re-use of public DIA proteomics datasets: from the PRIDE database to Expression Atlas

The paper introduces a pipeline to re-analyze public DIA proteomics datasets, integrating results into Expression Atlas to enhance data availability and utility.

Meta-analysis reveals consistent immune response patterns in COVID-19 infected patients at single-cell resolution

The paper performs a meta-analysis of single-cell RNA data from 9 studies to identify consistent immune response patterns in COVID-19 patients, finding consistent upregulation of type I interferon and downregulation of mitochondrial genes.

A proteomics sample metadata representation for multiomics integration, and big data analysis.

The paper introduces a standardized metadata format for proteomics datasets to improve reusability and integration across public repositories.

ISA API: An open platform for interoperable life science experimental metadata

The paper introduces the ISA API, a Python library for handling ISA-Tab and ISA-JSON metadata formats, enabling programmatic manipulation and interoperability in life science experiments.

UCSC Cell Browser: Visualize Your Single-Cell Data

The UCSC Cell Browser allows visualization of gene expression and metadata in single-cell datasets through a web interface and Python package.

User-friendly, scalable tools and workflows for single-cell analysis

The paper introduces an interactive scRNA-Seq analysis environment based on Galaxy, integrating ~70 functions for scalable and accessible single-cell data analysis.

BioContainers Registry: searching for bioinformatics tools, packages and containers

The paper introduces the BioContainers Registry and API to improve the findability, accessibility, interoperability, and reusability of bioinformatics tools and containers.

A Single-cell RNA-seq Training and Analysis Suite using the Galaxy Framework

The paper introduces a Galaxy-based suite for scRNA-seq analysis, offering workflows, training resources, and tools for preprocessing, normalization, and clustering across 10x and alternative platforms.

Scalable data analysis in proteomics and metabolomics using BioContainers and workflows engines.

The paper introduces a scalable approach for reproducible proteomics and metabolomics analysis using BioContainers and workflows engines like Galaxy and Nextflow.

Interoperable and scalable data analysis with microservices: Applications in Metabolomics

The paper introduces a microservices-based framework for scalable data analysis, validated in metabolomics, enabling dynamic scaling and integration of software tools.

Galaxy-Kubernetes integration: scaling bioinformatics workflows in the cloud

This paper integrates Galaxy with Kubernetes to enable scalable, cloud-agnostic bioinformatics workflows.

PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud

PhenoMeNal provides a cloud-based platform for metabolomics data analysis, integrating tools and workflows to enable reproducible and scalable research.