A single cell
expression database
that is truly accessible

Interactively
access 25106720 cells from published works

Instantly access and reanalyze a single cell database that is interactive, uniformly annotated and ready for visualization.

Query gene expression

Find differentially expressed genes between two groups

Find marker genes and enriched processes

Sub-cluster any cell populations

Leverage this single cell expression database for cell type prediction

Search populations that own similar expression profiles to your selected cells, and view their cell type labels.

Bioturing scRNA-seq software greatly accelerates and enables our research, through easy to use intuitive analytics, visualization and extensive database of curated and pre-processed experiments

Eugene Bolotin - Senior Bioinformatics Scientist, Kite Pharma

The BioTuring Browser is a game changer in the Immune Oncology field to speed up single cell data sharing among biologists, immunologists and bioinformaticians. Empowering collaboration in annotating cells, discovering unknown cell populations, cell states or cell interactions is crucial to draw the best picture ever of the highly heterogenous tumor microenvironment. Users have access to a growing public as well as their private knowledge base, which makes the BioTuring platform a swiss-army-knife for better understanding cells at the single cell level.

Molecular Oncology and Immunology Lab, IFOM

BBrowser allows biologists to handle scRNA-seq data without programming knowledge. Intuitive operation. Functions are updated. Public data can be imported. It is very helpful.

Researcher (Pharmacology), Chugai Pharmaceutical

I came across BBrowser while going through the Bioturing website and have been very impressed by the ease of use, capacity and capability of this unique platform. Within minutes from starting to use this tool, I was able to download single-cell sequencing datasets with metadata, obtain visualizations and biostatistical analyses including correlation and hierarchical clustering, analyse data by age, sex and pathology and carry differential gene expression analyses for my genes of interest. Overall, an amazing tool to have for every researcher engaged in scRNA approaches. Kudos to the developers for bringing this amazing platform to academics engaged in single-cell research. Looking forward to the addition of more studies/workflows and features to this already exciting software!

Anand Hardikar, Western Sydney University, Sydney Australia

The Bioturing Browser with single cell add-on provides one of the simplest interfaces for quickly moving from raw data to cluster analyses with minimal experience. The built-in HeraT alignment processes are remarkably quick and less computationally intensive than other scRNA-seq offerings.

Chris Ahuja - University of Toronto.

Bioturing Browser is an intuitive and powerful software for exploration and visualization of scRNA-Seq data. Its fast and easy access to the vast amounts of curated datasets is very helpful for our drug discovery research.

Niv Sabath - Senior Scientist, Compugen

BBrowser is an amazing software for analysis of single cell RNA sequencing data. It provides seamless integration with the analyzed data from R (not that it's required), and allows you to do differential expression, gene set enrichment, and pseudotime trajectory analysis very quickly and efficiently. I would also have to say that the "identify cell cluster" function, which compares your cell clusters to all the cell annotations available on the BBrowser database, has been amazing for me in identifying cell types that I didn't even know were present within my dataset. I highly recommend that everyone try out this software - both novice and veteran computational biologists alike will enjoy using it! The user interface is very intuitive, and the learning curve is not steep at all. Plus, Bioturing customer support is always available to help with any issues you may encounter during the course of your analysis.

Sanjid Shahriar, Agalliu Lab, Department of Neurology, Columbia University Irving Medical Center

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