Homology modeling

Applied sciences
Biological engineering
Biotechnology
Bioinformatics

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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

SPServer: split-statistical potentials for the analysis of protein structures and protein-protein interactions

Jaume Bonet Martinez

BackgroundStatistical potentials, also named knowledge-based potentials, are scoring functions derived from empirical data that can be used to evaluate the quality of protein folds and protein-protein interaction (PPI) structures. In previous works we deco ...

2021

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Naman Goel, Amit Sharma

Training datasets for machine learning often have some form of missingness. For example, to learn a model for deciding whom to give a loan, the available training data includes individuals who were given a loan in the past, but not those who were not. This ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

Symptom Prediction and Mortality Risk Calculation for COVID-19 Using Machine Learning

Nahal Mansouri, Sahand Jamal Rahi

Background: Early prediction of symptoms and mortality risks for COVID-19 patients would improve healthcare outcomes, allow for the appropriate distribution of healthcare resources, reduce healthcare costs, aid in vaccine prioritization and self-isolation ...

FRONTIERS MEDIA SA2021

Femtosecond laser-based optomechanical processes for permanent and high-precision fine alignment of optical systems

Saood Ibni Nazir

Miniaturization has been at the forefront of scientific research in the past decade covering diverse areas such as electronics, mechanics, and optics. While 'small is beautiful' may be a vast generalization, the true benefits of miniaturization are especia ...

EPFL2021

Structure determination of an amorphous drug through large-scale NMR predictions

David Lyndon Emsley, Pierrick Berruyer, Albert Hofstetter, Manuel Cordova, Federico Maria Paruzzo, Bruno Simões de Almeida, Martins Balodis

Knowledge of the structure of amorphous solids can direct, for example, the optimization of pharmaceutical formulations, but atomic-level structure determination in amorphous molecular solids has so far not been possible. Solid-state nuclear magnetic reson ...

Nature Research2021

Macro Modeling Technique for Integrally-Attached Timber Plates: Sensitivity Analysis

Yves Weinand, Aryan Rezaei Rad, Henry V. Burton

Using the Integral Mechanical Attachment (IMA) technique, a new macroscopic model has recently been introduced to simulate the structural behavior of segmented timber plates. The macro model is based on employing only beam and spring elements, which aims t ...

2021

MPGM: Scalable and Accurate Multiple Network Alignment

Matthias Grossglauser, Ehsan Kazemi

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

Model-Class Selection Using Clustering and Classification for Structural Identification and Prediction

Ian Smith, Sai Ganesh Sarvotham Pai, Masoud Sanayei

Structural identification using physics-based models and subsequent prediction have much potential to enhance civil infrastructure asset-management decision-making. Interpreting monitoring information in the presence of multiple uncertainty sources and sys ...

2021

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

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

Maurizio Molinari

2020