awesome-dl4g

Swiss-army knife of tools for a wide-range of genomics analysis tasks

A Python library for easy and efficient representation and analysis of biological data. (2022)

Biopython is a set of freely available tools for biological computation written in Python by an international team of developers.

[PyTorch] - General library for model interpretability in PyTorch

[TensorFlow] - Training and interpreting CNNs for predicting cell type-specific accessibility. (2021)

[PyTorch, TensorFlow, jax] - Open-source toolchain that democratizes the use of deep-learning in drug discovery, materials science, quantum chemistry, and biology. (2019)

Trained on the same dataset as DeepSEA to predict binarized epigenomic tracks from ENCODE and Roadmap. Added in a bi-directional LSTM layer after the convolutions and experimented with initializing convoultional filter weights with motifs.

One of the seminal convolutional based architectures trained to predict the binding of transcription factors and rna binding proteins.

in vitro RNA-binding protein assay of 244 RNA binding proteins. The dataset is downloaded as a single TSV file with RNA probes as rows and RNA binding proteins (RBP) as columns. Each entry in the table is an intensity measurement (can be normalized or raw) of the binding of each protein to each probe. There are over 244 RBP columns and 241,357 sequences spanning two sets (SetA and SetB)