This predictive model distinguishes between Relapsing-Remitting Multiple Sclerosis (RRMS) and Secondary Progressive Multiple Sclerosis (SPMS) using electronic health records collected at each hospital visit, with a focus on identifying transitions from RRMS to SPMS. It incorporates Conformal Prediction (CP) to quantify uncertainty and integrates E...xplainable AI (SHAP) to interpret the contribution of individual features to the predictions. The tool is in an anonymized form for research purposes. [see more]

• Akshai Parakkal Sreenivasan
  Uppsala University

  Medical Sciences, Clinical Chemistry

Suite of data science tools made by Fraunhofer ITMP

• Leonie von Berlin
  Other

**SNRApp** is an interactive web app to calculate the Signal-to-Noise Ratio (SNR) from spatial omics data. The user will need to upload an `anndata` and set the top and bottom percentile.

• Nima Rafati
  Uppsala University

  Medical Biochemistry and Microbiology

starbase is a database and toolkit for exploring of large transposable elements in Fungi

• Adrian Forsythe
  Uppsala University

  Organismal Biology

This app provides a reference database of proteins found in dried blood spots, based on published scientific studies. It serves as a tool for exploring the dried blood spot proteome.

• William Stauch
  KTH Royal Institute of Technology

  Protein Science

It helps to calculate sequencing depth required to get microbial genomes from metagenomics

• Lokeshwaran Manoharan
  Lund University

  NBIS, Faculty of Medicine

Apical hook kinetics analyzer: Shiny app to quantify and visualize kinematics based on angle measurements of Arabidopsis thaliana dark-grown seedlings extracted from time-series.

• Adrien Heymans
  Swedish University of Agricultural Sciences

  Forest Genetics and Plant Physiology

lipidomics

• Vikash Pandey
  Umeå University

  Molecular Biology

Suite of data science tools made by Fraunhofer ITMP (3rd Version)

• Leonie von Berlin
  Other

Test suite

• Yojana Gadiya
  Other

TurgoLab is an interactive, FEM-based simulation app for inflating 2D cellular structures from .geo files. It integrates the BVPy framework to enable intuitive biomechanical modeling of plant tissues under turgor pressure from the geometry made with Anatomeshr .

• Adrien Heymans
  Swedish University of Agricultural Sciences

  Forest Genetics and Plant Physiology

TissUUmaps demo

• Christophe Avenel
  Uppsala University

  Information Technology

• Isabelle Leo
  (KI) Karolinska institutet

  OnkPat

A converter of 2D plant anatomical data into finite element mesh (GEO) format.

• Adrien Heymans
  Swedish University of Agricultural Sciences

  Forest Genetics and Plant Physiology

A shiny application to process OLINK data. Outlier detection - filtering - statistical analysis - visualization - publication ready figures all at one place.

• Debojyoti Das
  Linköpings University

  Biomedical and Clinical Sciences (BKV)

Visualizations of the results from an interaction screen of 215 G protein-coupled receptors (GPCRs) and the receptor activity–modifying proteins (RAMPs). Companion app to ‘Multiplexed mapping of the interactome of GPCRs with receptor activity–modifying proteins’, https://doi.org/10.1126/sciadv.ado9959

• Leo Dahl
  KTH Royal Institute of Technology

  Affinity Proteomics

This site provides a databases of knockout designs targeting the entire Plasmodium berghei protein encoding genome using the PbHiT CRISPR system as described in Jonsdottir et al. DOI: https://doi.org/10.1101/2024.04.20.590404

• Johan Henriksson
  Umeå University

  Molecular Biology

Visualizations of the results from a selectivity screen of >400 antibodies targeting 215 G protein-coupled receptors (GPCRs). Companion app to ‘Multiplexed selectivity screening of anti-GPCR antibodies’, https://doi.org/10.1126/sciadv.adf9297

• Leo Dahl
  KTH Royal Institute of Technology

  Affinity Proteomics

ShinyCell app detailing cellular landscape of equine asthma

• Amanda Raine
  Uppsala University

  Medical Sciences

Biome-specific gene catalogues have been recovered for many environments using shotgun metagenomics, followed by assembly and gene calling on the assembled contigs. We recently proposed a novel mix-assembly strategy, combining individual and co-assembly approaches, and used this approach to assemble an extensive non-redundant gene set from 124 Bal...tic Sea metagenome samples. The Baltic Sea Gene Set (BAGS v1.1) comprises 66.53 million functionally and taxonomically annotated genes. To enable interactive exploration of this gene catalogue we have developed an RShiny application, BAGS-Shiny, that allows users to perform searches by sequence similarity (BLAST) and/or taxonomic and functional annotation. The gene catalogue and web application will serve as valuable tools for exploring microbial gene functions in brackish ecosystems. [see more]

• Johan Alfredéen
  Uppsala University

  SciLifeLab DC

This Shiny app provides a user-friendly interface for performing quick analysis of Olink data using OlinkAnalyze package. It allows for data upload, parameter customization, visualization of results, and exporting of analysis outputs.

• Jyotirmoy Das
  Linköpings University

  Biomedical and Clinical Sciences

KISSE is a species search engine that utilizes collagen sequences from eight different species to identify unknown samples.

• Hassan Gharibi
  (KI) Karolinska institutet

  Medical Biochemistry and Biophysics

Hosting page for AntiMicRobial KG and prediction models.

• Yojana Gadiya
  Other

Supplementary material to Sdougkou et al. 2024, "Longitudinal Exposomics in a Multiomic Wellness Cohort Reveals Distinctive and Dynamic Environmental Chemical Mixtures in Blood" Environmental Science & Technology, 58 (37) 16302–16315 https://doi.org/10.1021/acs.est.4c05235

• Stefano Papazian
  Stockholms University

  Environmental Science

Related publication: Li, Xiaofei, et al. "Profiling spatiotemporal gene expression of the developing human spinal cord and implications for ependymoma origin." Nature neuroscience 26.5 (2023): 891-901. https://doi.org/10.1038/s41593-023-01312-9

• Christophe Avenel
  Uppsala University

  Information Technology

Related publication: Kukanja, Petra, et al. "Cellular architecture of evolving neuroinflammatory lesions and multiple sclerosis pathology." Cell 187.8 (2024): 1990-2009. https://doi.org/10.1016/j.cell.2024.02.030

• Christophe Avenel
  Uppsala University

  Information Technology

Related publication: Andersson, Axel, et al. "Points2Regions: Fast, interactive clustering of imaging‐based spatial transcriptomics data." Cytometry Part A 105.9 (2024): 677-687. https://doi.org/10.1002/cyto.a.24884

• Christophe Avenel
  Uppsala University

  Information Technology

Related publication: Andersson, Axel, et al. "Cell segmentation of in situ transcriptomics data using signed graph partitioning." International Workshop on Graph-Based Representations in Pattern Recognition. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-42795-4_13

• Christophe Avenel
  Uppsala University

  Information Technology

Related publication: Ström, Peter, et al. "Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study." The Lancet Oncology 21.2 (2020): 222-232, https://doi.org/10.1016/S1470-2045(19)30738-7/

• Christophe Avenel
  Uppsala University

  Information Technology

DILI Predictor is an open-source app framework built specifically for human drug-induced liver injury (DILI). DILI Predictor employs eleven proxy-DILI labels from in vitro and in vivo datasets along with pharmacokinetic parameters, structural fingerprints and physicochemical parameters as features.

• Hamza Saeed
  Uppsala University

  Immunology, Genetics and Pathology

DICTrank Predictor is an open-source app framework built specifically for human drug-induced cardiotoxicity (DICT).DICTrank Predictor employs physicochemical parameters as feature. For more details look at https://www.biorxiv.org/content/10.1101/2023.10.15.562398v1

• Hamza Saeed
  Uppsala University

  Immunology, Genetics and Pathology

Dashboard for the R4A Expertise KG

• Yojana Gadiya
  Other

Explores interpretability for chest X-ray pathology predictions using methods—Grad-CAM, LIME, SHAP, and LRP. It provides heatmaps and evaluation metrics for better insights into the medical significance of predictions made by deep learning models.

• Mahbub Ul Alam
  Uppsala University

  Immunology, Genetics and Pathology

enrichedmassspec - a shiny app to visualize differentially expressed proteins (DEPs) and carry out enrichment analysis using different methods on Mass Spectrometry data from generated using spectronaut

• Debojyoti Das
  Linköpings University

  Biomedical and Clinical Sciences (BKV)

This is for exploring blood phenotypes in plasmogem screen data.

• Vikash Pandey
  Umeå University

  Molecular Biology

This Shiny app provides a user-friendly interface for performing Weighted Gene Co-expression Network Analysis (WGCNA) on RNA-seq/Microarray and DNA methylation (Array/Sequencing) data. It allows for data upload, parameter customization, visualization of results, and exporting of analysis outputs.

• Jyotirmoy Das
  Linköpings University

  Biomedical and Clinical Sciences

MMAtt-DTA: MultiModal Attention Drug-Target Affinity prediction

• Aleksandr Kushnir
  Other

  Public Health and Caring Sciences

Demo of Bayesian updating for teaching purposes. By Johan Henriksson, www.henlab.org. Source at https://github.com/henriksson-lab/demo_bayesupdate

• Johan Henriksson
  Umeå University

  Molecular Biology

Data exploration analysis tool. Load your csv data file and it will help to clean the data, report the missing/NA values (using pareto graph), perform a set of various statistical analyses (e.g., correlation, t-test, MW-test, KS-test, and more) resulting in tables and graphs.

• Ilona Szczot
  Linköpings University

  CSAN

Dashboard plotting the number of people in Sweden aged 0-19 who have have filled a prescription for ADHD medications each year.

• Arnold Kochari
  Uppsala University

  Institute for Genetics, Immunology, and Pathology

PK Predictor is an open-source app framework built specifically for predicting human and animal PK parameters

• Hamza Saeed
  Uppsala University

  Immunology, Genetics and Pathology

Clusetering of phenotype data

• Vikash Pandey
  Umeå University

  Molecular Biology

Comparing 4 types of the most common reference populations for child sex- and age-adjusted Body Mass Index (BMI)

• Maja Engsner
  Uppsala University

  Medical Cell Biology

Service that provides a REST Api to convert between different chemical notations. More info: https://github.com/DouglasConnect/ChemIdConvert.

• Hamza Saeed
  Uppsala University

  Immunology, Genetics and Pathology

New interventions to control malaria depend on a deep understanding of the parasite that causes the disease. The PlasmoGEM project produces free genetic tools for research on malaria parasites. We also use the reagents in genetic screens to identify parasite gene functions at scale. The purpose of this database is to share data generated by the p...roject. [see more]

• Vikash Pandey
  Umeå University

  Molecular Biology

Allows users to either upload an image file or take a picture using their webcam and get a prediction the chemical structure depicted in the image in SMILES notation.

• Arnold Kochari
  Uppsala University

  Institute for Genetics, Immunology, and Pathology

This app allows users to input an image (in jpeg format) of a flower and get a prediction on what type of flower it is from a machine learning model. Top three most likely flower types according to the model’s prediction are shown.

• Arnold Kochari
  Uppsala University

  Institute for Genetics, Immunology, and Pathology

peak cluster

• Vikash Pandey
  Umeå University

  Molecular Biology

In-silico Drug Repurposing Catalogue REMEDi4ALL (iDRC-R4A).

• Aleksandr Kushnir
  Other

  Public Health and Caring Sciences

Predicting chemical EC50 and EC10 ecotoxiticy values towards fish, aquatic invertebrate, and algae for a diverse set of effects using AI. Publication in Science Advances available through DOI: https://doi.org/10.1126/sciadv.adk6669

• Käll Styrbjörn
  Other

  Formerly at Chalmers

API for Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction. Refer to https://doi.org/10.3389/fphar.2018.01256 for the paper describing the tool.

• Hamza Saeed
  Uppsala University

  Immunology, Genetics and Pathology

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• Christophe Avenel
  Uppsala University

  Information Technology

IFNB single-cell transcriptomics data

• Roy Francis
  Other

  NBIS / Uppsala University

Trancriptom analysis for Suprcellfactories project

• Rasool Saghaleyni
  Chalmers University of Technology

  Systems and Synthetic Biology

scRNASeq of 55 samples from zebrafish brain. This project aims to characterize expression profile of different cell types.

• Nima Rafati
  Uppsala University

  Medical Biochemistry and Microbiology

The Mouse Organ Metabolite Atlas

• Tomasz Czuba
  Lund University

  Clinical Sciences, Cardiology

Power analysis for RNA-Seq experiment. Estimate number of samples required and more.

• Roy Francis
  Other

  NBIS / Uppsala University

Companion resource to the article, 'An online atlas of human plasma metabolite signatures of gut microbiome composition' by Dekkers et al

• Koen Dekkers
  Uppsala University

  Medical Sciences, Molecular epidemiology

Meta-analysis of skeletal muscle response to exercise and inactivity

• Nicolas Pillon
  (KI) Karolinska institutet

  Physiology and Pharmacology

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

This app is part of the Drug Repurposing Encyclopedia (DRE), a web server for systematic drug repurposing across 20 organisms. Refer to https://doi.org/10.1101/2023.03.10.532084 for the paper describing the tool.

• Lu Pan
  (KI) Karolinska institutet

  Institute of Environmental Medicine

Single Protein Localization

• Luay Aswad
  Other

  Karolinska Institutet / Oncology-Pathology

Correlation Network

• Luay Aswad
  Other

  Karolinska Institutet / Oncology-Pathology

Heatmap

• Luay Aswad
  Other

  Karolinska Institutet / Oncology-Pathology

Network

• Luay Aswad
  Other

  Karolinska Institutet / Oncology-Pathology

Data Download

• Luay Aswad
  Other

  Karolinska Institutet / Oncology-Pathology

Application that allows users to get predictive data about compound (Multiple Molecules)

• Hamza Saeed
  Uppsala University

  Immunology, Genetics and Pathology

Application that allows users to get predictive data about compound (Single Molecule)

• Hamza Saeed
  Uppsala University

  Immunology, Genetics and Pathology

Imminent myocardial infarction prediction model. In patients free from prior cardiovascular disease, we aimed to identify characteristics of an imminent first heart attack and design a prediction model.

• Stefan Gustafsson
  Uppsala University

  Medical Sciences, Clinical Epidemiology

Shiny app for displaying Dictyostelium discoideum RNA-seq and proteomics data, from the publication Edelbroek et al. 2024

• Jakub Westholm
  Stockholms University

  Biochemistry and Biophysics (DBB)

Model to predict the pKa of compounds

• Yojana Gadiya
  Other

All the browsable datasets from Lee et al 2024. "Open source, high throughput, targeted in situ transcriptomics"

• Marco Grillo
  Stockholms University

  Biochemistry and Biophysics (DBB)

This dashboard visualises the spread of COVID-19 in Sweden: confirmed cases, ICU admissions, and deaths between February 2020 and March 2023.

• Arnold Kochari
  Uppsala University

  Institute for Genetics, Immunology, and Pathology

Conformal regression model for predicting LogD for drug-like molecules, trained on ChEMBL version 33 with over 2.2M compounds using the CPSign software.

• Staffan Arvidsson McShane
  Uppsala University

  Pharmaceutical Biosciences

Predicts Ames Mutagenicity for a chemical structure using an SVM model with Signatures features via the CPSign modeling tool.

• Ola Spjuth
  Uppsala University

  Pharmaceutical Biosciences

RepurposeDrugs - an interactive web-based data portal and predictive platform for repurposing mono- and combination therapies.

• Aleksandr Kushnir
  Other

  Public Health and Caring Sciences

Modelling of cell-type signatures in the developmental human heart

• Christophe Avenel
  Uppsala University

  Information Technology

Human heart development ISS datasets generated for Lazar et.al 2024.

• Sergio Marco Salas
  Stockholms University

  Biochemistry and Biophysics (DBB)

Colorectal cancer usually metastasizes in the liver. Tumor cells can create two types of metastases: desmoplastic (DHGP) or replacement (RHGP). DHGP is characterized by a fibrotic rim that encapsulates the tumor cells and is associated with a better survival. In this project, we found two distinct areas in the rim: an outer area representing a ben...ign fibrotic reaction, and an inner area modified by the neighboring cancer cells. [see more]

• Axel Andersson
  Uppsala University

  IT

ALLIUM (ALL subtype Identification Using Machine learning) is a multimodal classifier of molecular subtypes in pediatric acute lymphoblastic leukemia, using DNA methylation (DNAm) and gene expression (GEX) data

• Mariya Lysenkova Wiklander
  Uppsala University

  Medical Sciences, SNP&SEQ Technology Platform

Demo of ROC curves, PR curves, and decision boundaries for teaching purposes, www.henlab.org. By Johan Henriksson. Source at https://github.com/henriksson-lab/demo_roc

• Johan Henriksson
  Umeå University

  Molecular Biology

Demo of xgboost and decision trees for teaching purposes. By Johan Henriksson, www.henlab.org. Source at https://github.com/henriksson-lab/demo_xgboost

• Johan Henriksson
  Umeå University

  Molecular Biology

API for model that predicts water–octanol distribution coefficient (logD) for chemical compounds: It is a proxy for the lipophilicity which is a major determinant of drug properties and overall suitability of drug candidates

• Hamza Saeed
  Uppsala University

  Immunology, Genetics and Pathology

A Shiny webapp for creating a Seurat object without programming expertise. Load a count matrix directory, interactively filter on metadata, view results, download Seurat object and results of differential gene expression testing.

• Rasmus Olofzon
  Lund University

  Lund Stem Cell Center

Demo of penalized linear models (elastic net) for teaching purposes. By Johan Henriksson, www.henlab.org. Source at https://github.com/henriksson-lab/demo_elasticnet

• Johan Henriksson
  Umeå University

  Molecular Biology

Demo of Bayesian linear models for teaching purposes. By Johan Henriksson, www.henlab.org. Source at https://github.com/henriksson-lab/demo_bayesianlinmod

• Johan Henriksson
  Umeå University

  Molecular Biology

Demo of markov chains and HMMs for teaching purposes. By Johan Henriksson, www.henlab.org. Source at https://github.com/henriksson-lab/demo_markovchain

• Johan Henriksson
  Umeå University

  Molecular Biology

Demo of the Poisson distribution, as relevant for NGS, for teaching purposes, www.henlab.org. By Johan Henriksson. Source at https://github.com/henriksson-lab/demo_poisson

• Johan Henriksson
  Umeå University

  Molecular Biology

Demo of statistical distributions for teaching purposes. By Johan Henriksson, www.henlab.org. Source at https://github.com/henriksson-lab/demo_statdist

• Johan Henriksson
  Umeå University

  Molecular Biology

Co-occurrence plots created using VOS viewer . There are three plots in total, each based on publications from a different SciLifeLab reporting group (i.e. affiliated researchers, infrastructure units, and SciLifeLab fellows). In each plot, we have considered the KeyWords Plus associated with each paper.

• Senthilkumar Panneerselvam
  Uppsala University

  Immunology, Genetics and Pathology

An app to check color balance in indexes for sequencing

• Alma Hansen
  Other

  Stockholm University, DBB / NGI

Shiny app for exploration of the Genome-wide PeptidoGlycan Profiling dataset of Vibrio cholerae mutant library. Access to this app is password protected while it is under peer review.

• Laura Alvarez
  Umeå University

  Molecular Biology

The mappings are provided for genes, proteins, metabolites, metabolic reactions, diseases, complexes and publications. This is a REST service for programmatic access to BridgeDb content, provided with interactive Swagger documentation using OpenAPI. For more info see https://www.bridgedb.org/.

• Arnold Kochari
  Uppsala University

  Institute for Genetics, Immunology, and Pathology

Supplemental interactive visualization of Adipose Tissue Gene expression after exercise. Built using flexdashboard.

• Leonidas Lundell
  Other

A tool to predict the risk of experiencing refractory/relapse disease within two years in DLBCL patients treated with R-CHOP.

• Hui Wan
  (KI) Karolinska institutet

  Medical Biochemistry and Biophysics, Immunology

A single shiny solution from sequencer data to pathway analysis

• Jyotirmoy Das
  Linköpings University

  Biomedical and Clinical Sciences

This Shiny app is used the course CB2030 Systems biology at KTH Royal Instute of Technology.

• Thanadol Sutantiwanichkul
  Other

  Uppsala University / Immunology, Genetics and Pathology

CellChat's Shiny app which allows interactive exploration of the cell-cell communication that are analyzed by the CellChat R-package

• Christophe Avenel
  Uppsala University

  Information Technology

CoViMAPP (CoViD-19 Meta-Analysis of Plasma Proteins) is a meta-analysis resource of plasma proteins' alterations in COVID-19.

• Haris Babacic
  (KI) Karolinska institutet

  Oncology-Pathology

OmicLoupe server. See https://quantitativeproteomics.org/omicloupe/ for info about OmicLoupe.

• Fredrik Levander
  Other

  NBIS / Lund University

3D igraph from tsne with variable genes (Data from Tiklova et al. 2016)

• Nanjiang Shu
  Other

  NBIS / Uppsala University

CitizenScience Project

• Nanjiang Shu
  Other

  NBIS / Uppsala University

Single cell RNA sequencing dataset associated with the manuscript "Amnion signals are essential for mesoderm formation in primates"

• Nanjiang Shu
  Other

  NBIS / Uppsala University

scRNA-seq data in: Small molecule screen identifies a salt-inducible kinase inhibitor inducing β-cell proliferation by transiently activating the unfolded protein response

• Nanjiang Shu
  Other

  NBIS / Uppsala University

Byrnes, Lauren E., et al. Lineage dynamics of murine pancreatic development at single-cell resolution

• Nanjiang Shu
  Other

  NBIS / Uppsala University

The Boreal Rhizospheric Atlas online tool was created to encourage exploration of a metatranscriptomic dataset of Norway spruce fine roots and their associated fungal communities from nutrient limited and nutrient enriched forest plots of the boreal region of Northern Sweden.

• Nicolas Delhomme
  Swedish University of Agricultural Sciences

  Forest Genetics and Plant Physiology