DCell 1.4 – Deep Neural Network simulating Cell Structure and Function

DCell 1.4

:: DESCRIPTION

DCell is a neural network model of budding yeast, a basic eukaryotic cell. The model structure corresponds exactly to a hierarchy of 2,526 cellular subsystems.

::DEVELOPER

Ma Laboratory / Ideker Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

DCell

:: MORE INFORMATION

Citation:

Ma J, Yu MK, Fong S, Ono K, Sage E, Demchak B, Sharan R, Ideker T.
Using deep learning to model the hierarchical structure and function of a cell.
Nat Methods. 2018 Apr;15(4):290-298. doi: 10.1038/nmeth.4627. Epub 2018 Mar 5. PMID: 29505029; PMCID: PMC5882547.

DeepVariant 1.2.0 – Highly Accurate Genomes With Deep Neural Networks

DeepVariant 1.2.0

:: DESCRIPTION

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

::DEVELOPER

DeepVariant team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

DeepVariant

:: MORE INFORMATION

Citation

Poplin R, Chang PC, Alexander D, Schwartz S, Colthurst T, Ku A, Newburger D, Dijamco J, Nguyen N, Afshar PT, Gross SS, Dorfman L, McLean CY, DePristo MA.
A universal SNP and small-indel variant caller using deep neural networks.
Nat Biotechnol. 2018 Nov;36(10):983-987. doi: 10.1038/nbt.4235. Epub 2018 Sep 24. PMID: 30247488.

gkm-DNN – gapped k-mer deep neural network

gkm-DNN

:: DESCRIPTION

gkm-DNN is a software which uses gapped k-mer frequency vector (gkm-fv) as input to train neural networks. gkm-DNN is designed for classification but can be easily extended to other problems such as regression and ranking.

::DEVELOPER

Shihua Zhang’s Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/Linux
R

:: DOWNLOAD

gkm-DNN

:: MORE INFORMATION

Citation

Cao Z, Zhang S.
Probe Efficient Feature Representation of Gapped K-mer Frequency Vectors from Sequences Using Deep Neural Networks.
IEEE/ACM Trans Comput Biol Bioinform. 2020 Mar-Apr;17(2):657-667. doi: 10.1109/TCBB.2018.2868071. Epub 2018 Aug 31. PMID: 30183639.

SINC – Scale-invariant Deep Neural-network Classifier for Bulk and Single-Cell RNA-seq.

SINC

:: DESCRIPTION

SINC is a deep-neural-network Classifier for Bulk and Single-Cell RNA-seq.

::DEVELOPER

Jun Li

:: SCREENSHOTS

N/A

:: REQUIREMENTS

MacOsX/ Linux / WIndows
Python

SINC

:: MORE INFORMATION

Citation

Bioinformatics, 36 (6), 1779-1784 2020 Mar 1
SINC: A Scale-Invariant Deep-Neural-Network Classifier for Bulk and Single-Cell RNA-seq Data
Chuanqi Wang , Jun Li