Publications related to Protein–protein interaction prediction

Interpretable Social Anchors for Human Trajectory Forecasting in Crowds

Alexandre Massoud Alahi, Parth Ashit Kothari

Human trajectory forecasting in crowds, at its core, is a sequence prediction problem with specific challenges of capturing inter-sequence dependencies (social interactions) and consequently predicting socially-compliant multimodal distributions. In recent ...

2021

Fast end-to-end learning on protein surfaces

Bruno Emanuel Ferreira De Sousa Correia, Freyr Sverrisson

Proteins' biological functions are defined by the geometric and chemical structure of their 3D molecular surfaces. Recent works have shown that geometric deep learning can be used on mesh-based representations of proteins to identify potential functional s ...

IEEE COMPUTER SOC2021

On the use of direct-coupling analysis with a reduced alphabet of amino acids combined with super-secondary structure motifs for protein fold prediction

Jaume Bonet Martinez

Direct-coupling analysis (DCA) for studying the coevolution of residues in proteins has been widely used to predict the three-dimensional structure of a protein from its sequence. We present RADI/raDIMod, a variation of the original DCA algorithm that grou ...

OXFORD UNIV PRESS2021

HP agents and biochemical interactions

Hikari Ananda Infinity Yoshihara

The intense but transient increase in nuclear magnetic resonance signal provided by dynamic nuclear polarization (DNP) has enabled a range of new applications, including rapid, minimally-invasive metabolic imaging at the second timescale. This chapter prov ...

Academic Press2021

Statistical physics of interacting proteins: Impact of dataset size and quality assessed in synthetic sequences

Anne-Florence Raphaëlle Bitbol, Pierre Mergny

Identifying protein-protein interactions is crucial for a systems-level understanding of the cell. Recently, algorithms based on inverse statistical physics, e.g., direct coupling analysis (DCA), have allowed to use evolutionarily related sequences to addr ...

2020

Graph-to-Graph Transformer for Transition-based Dependency Parsing

James Henderson, Alireza Mohammadshahi

We propose the Graph2Graph Transformer architecture for conditioning on and predicting arbitrary graphs, and apply it to the challenging task of transition-based dependency parsing. After proposing two novel Transformer models of transition-based dependenc ...

Association for Computational Linguistics2020

Will Cryo-Electron Microscopy Shift the Current Paradigm in Protein Structure Prediction?

Matteo Dal Peraro, Luciano Andres Abriata

Protein dynamics is undoubtedly a pervasive ingredient in all biological functions. However, structural biology has been strongly driven by a static-centered view of protein architecture. We argue that the recent advances of cryo-electron microscopy (EM) h ...

AMER CHEMICAL SOC2020

The functional proteome landscape of Escherichia coli

Camille Véronique Bernadette Goemans

Recent developments in high-throughput reverse genetics1,2 have revolutionized our ability to map gene function and interactions3,4,5,6. The power of these approaches depends on their ability to identify functionally associated genes, which elicit similar ...

2020

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Protein–protein interaction prediction

Cyclic thermomechanical behaviour of pile-soil interface and design methods for energy pile foundations

Interpretable Social Anchors for Human Trajectory Forecasting in Crowds

Fast end-to-end learning on protein surfaces

On the use of direct-coupling analysis with a reduced alphabet of amino acids combined with super-secondary structure motifs for protein fold prediction

HP agents and biochemical interactions

Statistical physics of interacting proteins: Impact of dataset size and quality assessed in synthetic sequences

Graph-to-Graph Transformer for Transition-based Dependency Parsing

Will Cryo-Electron Microscopy Shift the Current Paradigm in Protein Structure Prediction?

The functional proteome landscape of Escherichia coli

Approaching Ontology Alignment through Representation Learning to Bridge the Semantic Gap in Engineering Applications

Graph Chatbot

Chat with Graph Search

On the use of direct-coupling analysis with a reduced alphabet of amino acids combined with super-secondary structure motifs for protein fold prediction

Approaching Ontology Alignment through Representation Learning to Bridge the Semantic Gap in Engineering Applications

Interpretable Social Anchors for Human Trajectory Forecasting in Crowds

Will Cryo-Electron Microscopy Shift the Current Paradigm in Protein Structure Prediction?

Cyclic thermomechanical behaviour of pile-soil interface and design methods for energy pile foundations

Fast end-to-end learning on protein surfaces

HP agents and biochemical interactions

Statistical physics of interacting proteins: Impact of dataset size and quality assessed in synthetic sequences

The functional proteome landscape of Escherichia coli

Graph-to-Graph Transformer for Transition-based Dependency Parsing