Code and data sets for "DeepLC can predict retention times for peptides that carry as-yet unseen modifications"

Data Sets and Prediction Models Created using MLP, RNN and LSTM

Caracol, Gem Ralph
Choi, Jin-gyu
Park, Jae-sung
Son, Byung Chul
Jeon, Sin-soo
Lee, Kwan-sung
Shin, Yong Sam
Hwang, Dae-joon

September 2019

Binary Data Sets - 2018tbi219_shuffled3.csv and 2018tbi219_shuffled5.csv - these are stratified da...

dataset for "Rapid Prediction of Liquid Structure from a Single Molecular Configuration Using Deep Learning"

Chunhui Li

March 2023

The data sets are used to train, validate and test the PointNet-MD model for rapid prediction of rad...

Code and data for "Accuracy and data efficiency in deep learning models of protein expression", Nature Communications

Nikolados, Evangelos-Marios
Wongprommoon, Arin
Mac Aodha, Oisin
Cambray, Guillaume
Oyarzún, Diego A.

November 2022

Code and data for "Accuracy and data efficiency in deep learning models of protein expression", Natu...

Code and data sets for "DeepLC can predict retention times for peptides that carry as-yet unseen modifications"

Bouwmeester, Robbin
Gabriels, Ralf
Hulstaert, Niels
Martens, Lennart
Degroeve, Sven

March 2020

Code used to prepare the data sets, calibrate retention times, generate DeepLC models, make predicti...

DeepLC can predict retention times for peptides that carry as-yet unseen modifications

Bouwmeester, Robbin
Gabriels, Ralf
Hulstaert, Niels
Martens, Lennart
Degroeve, Sven

January 2021

DeepLC, a deep learning-based peptide retention time predictor, can predict retention times for unmo...

dlomix-serving/Deeplc_hela_hf

Lautenbacher Ludwig

January 2023

The DeepLC model 'full_hc_hela_hf_psms_aligned_1fd8363d9af9dcad3be7553c39396960.hdf5' taken from htt...

Improved Peptide Retention Time Prediction in Liquid Chromatography through Deep Learning

Chunwei Ma (3751129)
Yan Ren (149348)
Jiarui Yang (3219708)
Zhe Ren (558949)
Huanming Yang (5905)
Siqi Liu (6569)

August 2018

The accuracy of peptide retention time (RT) prediction model in liquid chromatography (LC) is still ...

Dataset for manuscript "Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning"

Kroll, Alexander
Rousset, Yvan
Hu, Xiao-Pan
Liebrand, Nina
Lercher, Martin

November 2022

Dataset for the github repository containing the code for the manuscript "Turnover number prediction...

A Deep Learning Approach to Antibiotic Discovery: Chemprop Model

Jonathan Stokes
Kevin Yang
Kyle Swanson
Wengong Jin
Tommi Jaakkola
Regina Barzilay
James J. Collins

May 2022

This record contains the checkpoint for a Chemprop model trained to predict the probability that a m...

Deep model predictive control of gene expression in thousands of single cells

Jean-Baptiste Lugagne
Caroline M. Blassick
Mary J. Dunlop

July 2023

Experimental data, training datasets, and trained models for our study on deep model predictive cont...

Code and data sets for "MS²Rescore: Data-driven rescoring dramatically boosts immunopeptide identification rates"

Declercq Arthur
Bouwmeester Robbin
Hirschler Aurélie
Carapito Christine
Degroeve Sven
Martens Lennart
Gabriels Ralf

November 2021

Code used to prepare data sets, train and evaluate new MS²PIP models, evaluate MS²Rescore for immuno...

AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics

Zeng, W.
Zhou, X.
Willems, S.
Ammar, C.
Wahle, M.
Bludau, I.
Voytik, E.
Strauss, M.
Mann, M.

November 2022

Machine learning and in particular deep learning (DL) are increasingly important in mass spectrometr...

Chromatographic retention time prediction for posttranslationally modified peptides

Moruz, Luminita
Staes, An
Foster, Joseph M
Hatzou, Maria
Timmerman, Evy
Martens, Lennart
Käll, Lukas

January 2012

Retention time prediction of peptides in liquid chromatography has proven to be a valuable tool for ...

Predictive modeling of moonlighting DNA-binding proteins

Varghese Dana Mary
Nussinov Ruth
Ahmad Shandar

November 2022

This repository contains the codes used for the prediction of moonlighting proteins in the paper "Pr...

Prediction of LCMSMS properties of peptides from sequence by deep learning

Guan, Shenheng
Moran, Michael F.
Ma, Bin

June 2019

Highlights Deep learning models for prediction of LCMSMS properties In Brief Statement Indexe...

Data Sets and Prediction Models Created using MLP, RNN and LSTM

Caracol, Gem Ralph
Choi, Jin-gyu
Park, Jae-sung
Son, Byung Chul
Jeon, Sin-soo
Lee, Kwan-sung
Shin, Yong Sam
Hwang, Dae-joon

September 2019

Binary Data Sets - 2018tbi219_shuffled3.csv and 2018tbi219_shuffled5.csv - these are stratified da...

dataset for "Rapid Prediction of Liquid Structure from a Single Molecular Configuration Using Deep Learning"

Chunhui Li

March 2023

The data sets are used to train, validate and test the PointNet-MD model for rapid prediction of rad...

Code and data for "Accuracy and data efficiency in deep learning models of protein expression", Nature Communications

Nikolados, Evangelos-Marios
Wongprommoon, Arin
Mac Aodha, Oisin
Cambray, Guillaume
Oyarzún, Diego A.

November 2022

Code and data for "Accuracy and data efficiency in deep learning models of protein expression", Natu...

Code and data sets for "DeepLC can predict retention times for peptides that carry as-yet unseen modifications"

Bouwmeester, Robbin
Gabriels, Ralf
Hulstaert, Niels
Martens, Lennart
Degroeve, Sven

March 2020

Code used to prepare the data sets, calibrate retention times, generate DeepLC models, make predicti...

DeepLC can predict retention times for peptides that carry as-yet unseen modifications

Bouwmeester, Robbin
Gabriels, Ralf
Hulstaert, Niels
Martens, Lennart
Degroeve, Sven

January 2021

DeepLC, a deep learning-based peptide retention time predictor, can predict retention times for unmo...

dlomix-serving/Deeplc_hela_hf

Lautenbacher Ludwig

January 2023

The DeepLC model 'full_hc_hela_hf_psms_aligned_1fd8363d9af9dcad3be7553c39396960.hdf5' taken from htt...

Improved Peptide Retention Time Prediction in Liquid Chromatography through Deep Learning

Chunwei Ma (3751129)
Yan Ren (149348)
Jiarui Yang (3219708)
Zhe Ren (558949)
Huanming Yang (5905)
Siqi Liu (6569)

August 2018

The accuracy of peptide retention time (RT) prediction model in liquid chromatography (LC) is still ...

Dataset for manuscript "Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning"

Kroll, Alexander
Rousset, Yvan
Hu, Xiao-Pan
Liebrand, Nina
Lercher, Martin

November 2022

Dataset for the github repository containing the code for the manuscript "Turnover number prediction...

A Deep Learning Approach to Antibiotic Discovery: Chemprop Model

Jonathan Stokes
Kevin Yang
Kyle Swanson
Wengong Jin
Tommi Jaakkola
Regina Barzilay
James J. Collins

May 2022

This record contains the checkpoint for a Chemprop model trained to predict the probability that a m...

Deep model predictive control of gene expression in thousands of single cells

Jean-Baptiste Lugagne
Caroline M. Blassick
Mary J. Dunlop

July 2023

Experimental data, training datasets, and trained models for our study on deep model predictive cont...

Code and data sets for "MS²Rescore: Data-driven rescoring dramatically boosts immunopeptide identification rates"

Declercq Arthur
Bouwmeester Robbin
Hirschler Aurélie
Carapito Christine
Degroeve Sven
Martens Lennart
Gabriels Ralf

November 2021

Code used to prepare data sets, train and evaluate new MS²PIP models, evaluate MS²Rescore for immuno...

AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics

Zeng, W.
Zhou, X.
Willems, S.
Ammar, C.
Wahle, M.
Bludau, I.
Voytik, E.
Strauss, M.
Mann, M.

November 2022

Machine learning and in particular deep learning (DL) are increasingly important in mass spectrometr...

Chromatographic retention time prediction for posttranslationally modified peptides

Moruz, Luminita
Staes, An
Foster, Joseph M
Hatzou, Maria
Timmerman, Evy
Martens, Lennart
Käll, Lukas

January 2012

Retention time prediction of peptides in liquid chromatography has proven to be a valuable tool for ...

Predictive modeling of moonlighting DNA-binding proteins

Varghese Dana Mary
Nussinov Ruth
Ahmad Shandar

November 2022

This repository contains the codes used for the prediction of moonlighting proteins in the paper "Pr...

Prediction of LCMSMS properties of peptides from sequence by deep learning

Guan, Shenheng
Moran, Michael F.
Ma, Bin

June 2019

Highlights Deep learning models for prediction of LCMSMS properties In Brief Statement Indexe...

Data Sets and Prediction Models Created using MLP, RNN and LSTM

Caracol, Gem Ralph
Choi, Jin-gyu
Park, Jae-sung
Son, Byung Chul
Jeon, Sin-soo
Lee, Kwan-sung
Shin, Yong Sam
Hwang, Dae-joon

September 2019

Binary Data Sets - 2018tbi219_shuffled3.csv and 2018tbi219_shuffled5.csv - these are stratified da...

dataset for "Rapid Prediction of Liquid Structure from a Single Molecular Configuration Using Deep Learning"

Chunhui Li

March 2023

The data sets are used to train, validate and test the PointNet-MD model for rapid prediction of rad...

Code and data for "Accuracy and data efficiency in deep learning models of protein expression", Nature Communications

Nikolados, Evangelos-Marios
Wongprommoon, Arin
Mac Aodha, Oisin
Cambray, Guillaume
Oyarzún, Diego A.

November 2022

Code and data for "Accuracy and data efficiency in deep learning models of protein expression", Natu...

Code and data sets for "DeepLC can predict retention times for peptides that carry as-yet unseen modifications"

Abstract

Extracted data

Code and data sets for "DeepLC can predict retention times for peptides that carry as-yet unseen modifications"

Abstract

Extracted data

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