Concept

Protein–protein interaction prediction

Related publications (171)

MPGM: Scalable and Accurate Multiple Network Alignment

Protein-protein interaction (PPI) network alignment is a canonical operation to transfer biological knowledge among species. The alignment of PPI-networks has many applications, such as the prediction of protein function, detection of conserved network mot ...

IEEE COMPUTER SOC2020

Bayesian regression explains how human participants handle parameter uncertainty

Michael Herzog, Jean-Pascal Théodor Pfister, Maya Anna Jastrzebowska, Mattew Pachai

Author summary How do humans make prediction when the critical factor that influences the quality of the prediction is hidden? Here, we address this question by conducting a simple psychophysical experiment in which participants had to extrapolate a parabo ...

2020

Predictive Reliability and Fault Management in Exascale Systems

David Atienza Alonso, Marina Zapater Sancho

Performance and power constraints come together with Complementary Metal Oxide Semiconductor technology scaling in future Exascale systems. Technology scaling makes each individual transistor more prone to faults and, due to the exponential increase in the ...

2020

Deep learning approach for quantification of organelles and misfolded polypeptide delivery within degradative compartments

Maurizio Molinari

Endolysosomal compartments maintain cellular fitness by clearing dysfunctional organelles and proteins from cells. Modulation of their activity offers therapeutic opportunities. Quantification of cargo delivery to and/or accumulation within endolysosomes i ...

2020

Fatigue life modeling and prediction methods for composite materials and structures—Past, present, and future prospects

Anastasios Vassilopoulos

This chapter aims to provide an overview of the fatigue life modeling and prediction methods for composite materials and structures, recalling methods used in the past, discovering the present status, and attempting to foresee future trends. ...

Elsevier2019

Phylogenetic correlations can suffice to infer protein partners from sequences

Anne-Florence Raphaëlle Bitbol

Author summary Many biologically important protein-protein interactions are conserved over evolutionary time scales. This leads to two different signals that can be used to computationally predict interactions between protein families and to identify speci ...

2019

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning

Bruno Emanuel Ferreira De Sousa Correia, Michael Bronstein, Pablo Gainza Cirauqui, Freyr Sverrisson

Predicting interactions between proteins and other biomolecules solely based on structure remains a challenge in biology. A high-level representation of protein structure, the molecular surface, displays patterns of chemical and geometric features that fin ...

2019

A comparative study on network alignment techniques

Thanh Trung Huynh, Thành Tâm Nguyên, Chi Thang Duong

Network alignment is a method to align nodes that belong to the same entity from different networks. A well-known application of network alignment is to map user accounts from different social networks that belong to the same person. As network alignment h ...

PERGAMON-ELSEVIER SCIENCE LTD2019

A further leap of improvement in tertiary structure prediction in CASP13 prompts new routes for future assessments

Matteo Dal Peraro, Luciano Andres Abriata, Giorgio Elikem Tamo

We present our assessment of tertiary structure predictions for hard targets in Critical Assessment of Structure Prediction round 13 (CASP13). The analysis includes (a) assignment and discussion of best models through scores-aided visual inspection of mode ...

WILEY2019

Micro-Two-Phase Electronics Cooling: Finally on Its Way

John Richard Thome

In this paper, I will present an abridged overview of what is presented in my keynote lecture. I will recount some of the initial history of microchannel two-phase flow and boiling work by others that enticed me to join into the development of this field a ...

IEEE2019

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