Search research articles
Contact Us
Filters
Showing results (1-10 of 34) with videos related to
Page
of 4
Sort By:
Nature Communications
|
June 9, 2019
Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index
Gabriele Orlando, Daniele Raimondi, Wim F Vranken
Plos One
|
July 11, 2015
An Evolutionary View on Disulfide Bond Connectivities Prediction Using Phylogenetic Trees and a Simple Cysteine Mutation Model
Daniele Raimondi, Gabriele Orlando, Wim F Vranken
Bioinformatics (Oxford, England)
|
December 11, 2014
Clustering-based model of cysteine co-evolution improves disulfide bond connectivity prediction and reduces homologous sequence requirements
Daniele Raimondi, Gabriele Orlando, Wim F Vranken
Plos Computational Biology
|
May 1, 2020
Insight into the protein solubility driving forces with neural attention
Daniele Raimondi, Gabriele Orlando, Piero Fariselli, et al.
Bioinformatics (Oxford, England)
|
March 21, 2024
Integrating physics in deep learning algorithms: a force field as a PyTorch module
Gabriele Orlando, Luis Serrano, Joost Schymkowitz, et al.
Scientific Reports
|
November 16, 2019
Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis
Daniele Raimondi, Gabriele Orlando, Wim F Vranken, et al.
Human Mutation
|
September 27, 2016
Investigating the Molecular Mechanisms Behind Uncharacterized Cysteine Losses from Prediction of Their Oxidation State
Daniele Raimondi, Gabriele Orlando, Joris Messens, et al.
Bioinformatics (Oxford, England)
|
April 24, 2018
Ultra-fast global homology detection with Discrete Cosine Transform and Dynamic Time Warping
Daniele Raimondi, Gabriele Orlando, Yves Moreau, et al.
Nucleic Acids Research
|
May 28, 2020
ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values
Gabriele Orlando, Daniele Raimondi, Luciano Porto Kagami, et al.
Journal of Molecular Biology
|
April 26, 2022
Prediction of Disordered Regions in Proteins with Recurrent Neural Networks and Protein Dynamics
Gabriele Orlando, Daniele Raimondi, Francesco Codicè, et al.
Page
of 4
Search research articles
Search
Showing results (1-10 of 34) with videos related to
Sort By:
Page
of 4
Nature Communications
|
June 9, 2019
Auto-encoding NMR chemical shifts from their native vector space to a residue-level biophysical index
Gabriele Orlando, Daniele Raimondi, Wim F Vranken
Plos One
|
July 11, 2015
An Evolutionary View on Disulfide Bond Connectivities Prediction Using Phylogenetic Trees and a Simple Cysteine Mutation Model
Daniele Raimondi, Gabriele Orlando, Wim F Vranken
Bioinformatics (Oxford, England)
|
December 11, 2014
Clustering-based model of cysteine co-evolution improves disulfide bond connectivity prediction and reduces homologous sequence requirements
Daniele Raimondi, Gabriele Orlando, Wim F Vranken
Plos Computational Biology
|
May 1, 2020
Insight into the protein solubility driving forces with neural attention
Daniele Raimondi, Gabriele Orlando, Piero Fariselli, et al.
Bioinformatics (Oxford, England)
|
March 21, 2024
Integrating physics in deep learning algorithms: a force field as a PyTorch module
Gabriele Orlando, Luis Serrano, Joost Schymkowitz, et al.
Scientific Reports
|
November 16, 2019
Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis
Daniele Raimondi, Gabriele Orlando, Wim F Vranken, et al.
Human Mutation
|
September 27, 2016
Investigating the Molecular Mechanisms Behind Uncharacterized Cysteine Losses from Prediction of Their Oxidation State
Daniele Raimondi, Gabriele Orlando, Joris Messens, et al.
Bioinformatics (Oxford, England)
|
April 24, 2018
Ultra-fast global homology detection with Discrete Cosine Transform and Dynamic Time Warping
Daniele Raimondi, Gabriele Orlando, Yves Moreau, et al.
Nucleic Acids Research
|
May 28, 2020
ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values
Gabriele Orlando, Daniele Raimondi, Luciano Porto Kagami, et al.
Journal of Molecular Biology
|
April 26, 2022
Prediction of Disordered Regions in Proteins with Recurrent Neural Networks and Protein Dynamics
Gabriele Orlando, Daniele Raimondi, Francesco Codicè, et al.
Page
of 4