NucPosDB is a manually curated database based on more than 400 publications reporting experimental nucleosome maps in vivo across different cell types and conditions, cell-free DNA datasets in human patients and model organisms as well as software for computational analysis  and  modelling of nucleosome positioning and “nucleosomics” analysis for medical diagnostics.


Sequenced cell-free DNA (cfDNA) datasets

This is the most recent addition to the database, which is expanding quickly. It contains sequenced cell-free DNA (cfDNA) from body liquids such as blood plasma, urine, cerebrospinal liquid, etc. 


Experimental nucleosome maps in vivo  

This section of the database is devoted to experimental datasets such as MNase-seq, MNase-assisted H3 ChIP-seq, chemical mapping, etc, conducted in cells or tissues. 

 

 

COMPUTATIONAL ANALYSIS:

 

Prediction of nucleosome positioning

This repository contains software tools for prediction of nucleosome positioning from DNA sequence based on biophysics or bioinformatics approaches

 

 

 

Analysis of in vivo nucleosome positioning

This repository currently contains software solutions for analysis of MNase-seq, chemical nucleosome mapping and other experimental techniques to map nucleosomes

 

 

 

Tools for analysis of sequenced cfDNA

This repository is devoted to bioinformatics tools for the basic analysis of cfDNA, such as determining mutations, copy number variations, DNA methylation and nucleosome positioning reconstruction.


*How to add: To suggest a new dataset or software for inclusion in this database please email [email protected].

**How to cite: The “official” publication describing NucPosDB is currently in preparation. Meanwhile please site these papers:

Teif V.B. and Clarkson C.T. (2019) Nucleosome Positioning. In Encyclopedia of Bioinformatics and Computational Biology (Ed.: S. Ranganathan, M. Gribskov, K. Nakai, and C. Schönbach), vol. 2, pp. 308–317. Oxford: Academic Press

Teif V.B. (2016). Nucleosome positioning: resources and tools online. Briefings in Bioinformatics. 17, 745-757 | Open access article