Model group Models Authors Contributed by Type Cite as License Tags
Model group Models Authors Contributed by Type Cite as License Tags
APARENT 2 Nicholas Bogard et al. Shabnam Sadegharmaki et al. None https://doi.org/10.1101/300061 MIT
AttentiveChrome 55 Ritambhara Singh et al. Jack Lanchantin et al. pytorch https://doi.org:/10.1101/329334 MIT RNA expression
BPNet-OSKN 1 Ziga Avsec Ziga Avsec None https://doi.org/10.1101/737981 MIT DNA binding
BPNet_Dmel_OreR_2to3hr_ZDTBCG 1 Melanie Weilert and Kaelan Brennan Melanie Weilert and Kaelan Brennan None https://doi.org/10.1101/2022.12.20.520743 MIT
Basenji 1 David R. Kelley Ziga Avsec tensorflow https://doi.org/10.1101/gr.227819.117 Apache License v2 RNA expression, Histone modification, DNA accessibility
Basset 1 David R. Kelley Roman Kreuzhuber pytorch https://doi.org/10.1101/gr.200535.115 MIT DNA accessibility
CleTimer 2 Leohnard Wachutka et al. Leohnard Wachutka et al. None Apache License v2 RNA splicing
CpGenie 51 Haoyang Zeng Roman Kreuzhuber custom, keras https://doi.org/10.1093/nar/gkx177 Apache License v2 DNA methylation
DeepBind 927 Babak Alipanahi et al. Johnny Israeli keras https://doi.org/10.1038/nbt.3300 BSD 3-Clause DNA binding
DeepCpG_DNA 5 Christof Angermueller Roman Kreuzhuber keras https://doi.org/10.1186/s13059-017-1189-z
https://doi.org/10.5281/zenodo.1094823
MIT DNA methylation
DeepFlyBrain 1 Ibrahim Ihsan Taskiran et al. Ibrahim Ihsan Taskiran et al. None TBA MIT
DeepLiver 3 Carmen Bravo et al. Carmen Bravo et al. None Bravo
González-Blas
Carmen.
(2022).
Enhancer
grammar
of
liver
cell
types
and
hepatocyte
zonation
states.
https://doi.org/10.1101/2022.12.08.519575
Other / Non-commercial (see LICENSE.txt)
DeepMEL 3 Ibrahim Ihsan Taskiran et al. Ibrahim Ihsan Taskiran et al. None https://doi.org/10.1101/gr.260844.120
https://doi.org/10.1101/2019.12.21.885806
MIT
DeepSEA 3 Jian Zhou et al. Roman Kreuzhuber None, pytorch https://doi.org/10.1038/s41588-018-0160-6
https://doi.org/10.1038/nmeth.3547
Non-comercial, CC-BY 3.0 Histone modification, DNA binding, DNA accessibility
DeepSTARR 1 Bernardo P. de Almeida Bernardo P. de Almeida None https://doi.org/10.1101/2021.10.05.463203 MIT
Divergent421 1 Nancy Xu Nancy Xu None MIT DNA accessibility
FactorNet 30 Daniel Quang et al. Ziga Avsec keras https://doi.org/10.1101/151274 MIT DNA binding
Framepool 1 Alexander Karollus Alexander Karollus None MIT Translation
HAL 1 Alexander B. Rosenberg Jun Cheng et al. None https://doi.org/10.1016/j.cell.2015.09.054 MIT RNA splicing
KipoiSplice 2 Ziga Avsec et al. Ziga Avsec et al. sklearn https://doi.org/10.1101/375345 MIT RNA splicing
MMSplice 5 Jun Cheng Jun Cheng custom MIT RNA splicing
MPRA-DragoNN 2 Rajiv Movva, Surag Nair Rajiv Movva, Surag Nair None https://doi.org/10.1101/393926 MIT RNA expression
MaxEntScan 2 Gene Yeo et al. Jun Cheng et al. None https://doi.org/10.1089/1066527041410418 MIT RNA splicing
OptMRL 1 Frederick Korbel, Ekaterina Eroshok, Uwe Ohler Frederick Korbel, Ekaterina Eroshok, Uwe Ohler None https://doi.org/10.1101/2023.06.02.543405 GPL-3
Optimus_5Prime 1 Paul J. Sample Ban Wang None https://doi.org/10.1101/310375 MIT Translation
SeqVec 3 Michael Heinzinger, Ahmed Elnaggar et al. Michael Heinzinger, Ahmed Elnaggar et al. None https://doi.org/10.1101/614313
https://doi.org:/10.1101/614313
MIT Protein properties, Protein structure
SiSp 1 Lara Urban Lara Urban keras https://doi.org/10.1101/328138 MIT RNA splicing
TREDNet 4 Sanjarbek Hudaiberdiev Sanjarbek Hudaiberdiev None https://medrxiv.org/cgi/content/short/2022.05.13.22275035v1 CC-BY-ND
Xpresso 5 Vikram Agarwal Vikram Agarwal None https://doi.org/10.1016/j.celrep.2020.107663 MIT
a2z-chromatin 2 Travis Wrightsman Travis Wrightsman None https://doi.org/10.1101/2021.11.11.468292 MIT DNA accessibility, DNA methylation, Plants
deepTarget 1 Byunghan Lee et al. Ziga Avsec None https://arxiv.org/pdf/1603.09123.pdf GPL-v3 RNA binding
epidermal_basset 60 Daniel Kim Daniel Kim None https://doi.org:/... MIT
extended_coda 1 Pang Wei Koh et al. Johnny Israeli keras https://doi.org/10.1093/bioinformatics/btx243 MIT Histone modification
labranchor 1 Joseph M. Paggi et al. Jun Cheng keras https://doi.org/10.1101/185868 CC BY-NC 4.0 RNA splicing
lsgkm-SVM 322 Dongwon Lee Roman Kreuzhuber None https://doi.org/10.1093/bioinformatics/btw142 MIT DNA binding
pwm_HOCOMOCO 600 Ivan V. Kulakovskiy Ziga Avsec keras https://doi.org/10.1093/nar/gkv1249 MIT DNA binding
rbp_eclip 102 Ziga Avsec Ziga Avsec keras https://doi.org/10.1093/bioinformatics/btx727 MIT RNA binding
scbasset 1 Han Yuan, David R. Kelley Han Yuan keras https://doi.org/10.1101/gr.200535.115 Apache License 2.0 scATAC accessibility

Kipoi models

CircleCI DOI

This repository hosts predictive models for genomics and serves as a model source for Kipoi. Each folder containing model.yaml is considered to be a single model.

Contributing models

  1. Install kipoi:

    pip install kipoi
    

  2. Run kipoi ls. This will checkout the kipoi/models repo to ~/.kipoi/models)

  3. Follow the instructions on contributing/Getting started.

Using models (to predict, score variants, build new models)

To explore available models, visit http://kipoi.org/models. See kipoi/README.md and docs/using getting started for more information on how to programatically access the models from this repository using CLI, python or R.

Configuring local storage location

This model source (https://github.com/kipoi/models) is included in the Kipoi config file (~/.kipoi/config.yaml) by default:

# ~/.kipoi/config.yaml
model_sources:
    kipoi:
        type: git-lfs
        remote_url: [email protected]:kipoi/models.git
        local_path: ~/.kipoi/models/
        auto_update: True

If you wish to keep the models stored elsewhere, edit the local_path accordingly.