4.7 Article

AggBERT: Best in Class Prediction of Hexapeptide Amyloidogenesis with a Semi-Supervised ProtBERT Model

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Multidisciplinary Sciences

Deep learning model calibration for improving performance in class-imbalanced medical image classification tasks

Sivaramakrishnan Rajaraman et al.

Summary: In this study, the effect of model calibration on the performance of medical image classification tasks was systematically analyzed. The results show that calibration can significantly improve performance at the default classification threshold, but the differences are not significant at the PR-guided threshold. This observation holds for different image modalities and degrees of class imbalance.

PLOS ONE (2022)

Article Engineering, Biomedical

hyOPTXg: OPTUNA hyper-parameter optimization framework for predicting cardiovascular disease using XGBoost

Polipireddy Srinivas et al.

Summary: This research proposes an expert model called hyOPTXg, which utilizes an optimized XGBoost classifier to predict cardiovascular disease. Through hyper-parameter tuning and training with the OPTUNA framework, the system achieves better results compared to other systems on various datasets.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2022)

Article Computer Science, Interdisciplinary Applications

Machine learning based predictive model for the analysis of sequence activity relationships using protein spectra and protein descriptors

Adam Mckenna et al.

Summary: Accurately predicting the effects of protein mutations is a key focus in protein engineering. This study evaluates encoding strategies for protein sequences using the Amino Acid Index database. By transforming the indices into their spectral form and combining them with protein structural and physiochemical descriptors, as well as using the Partial Least Squares Regression algorithm, predictive models with improved quality were built. The findings highlight the utility of this encoding strategy in identifying the Sequence-Activity-Relationship (SAR).

JOURNAL OF BIOMEDICAL INFORMATICS (2022)

Article Biochemistry & Molecular Biology

Effects of Mutations and Post-Transla- tional Modifications on a-Synuclein In Vitro Aggregation

Samantha X. Pancoe et al.

Summary: Fibrillar aggregates of the a-synuclein protein are characteristic of Parkinson's Disease and related neurodegenerative disorders. This study presents a comprehensive collection of data on the effects of mutations and post-translational modifications on the aggregation rate of aS, as well as the impact of fluorescent labeling on aS aggregation. The data analysis provides insights into the structural characteristics of aS and can be used to interpret aggregation experiments and inform computational models of aggregation.

JOURNAL OF MOLECULAR BIOLOGY (2022)

Article Computer Science, Artificial Intelligence

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning

Ahmed Elnaggar et al.

Summary: Computational biology and bioinformatics provide valuable data for the development of language models in natural language processing. In this study, six different models were trained on protein sequence data and the resulting embeddings were used for various protein structure prediction tasks, demonstrating their advantages over traditional methods.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2022)

Article Multidisciplinary Sciences

Biomolecular simulation based machine learning models accurately predict sites of tolerability to the unnatural amino acid acridonylalanine

Sam Giannakoulias et al.

Summary: The newly developed scoring functions accurately predict the impact of unnatural amino acids on protein yield and solubility, revealing the crucial role in predicting mutation tolerance. This study demonstrates that extracting features from structural models and applying them to machine learning can accurately predict diverse and abstract biological phenomena in biological systems.

SCIENTIFIC REPORTS (2021)

Article Chemistry, Multidisciplinary

Rational design of thioamide peptides as selective inhibitors of cysteine protease cathepsin L

Hoang Anh T. Phan et al.

Summary: This study demonstrates that specific peptidyl protease inhibitors can be designed by strategically placing a thioamide, improving the stability and selectivity of the peptides against cathepsin family cysteine proteases. One peptide, R-1A(S), stabilized with thioamide, showed inhibition of all five cathepsins while displaying over 25-fold specificity for Cts L against the other cathepsins.

CHEMICAL SCIENCE (2021)

Article Biochemistry & Molecular Biology

WALTZ-DB 2.0: an updated database containing structural information of experimentally determined amyloid-forming peptides

Nikolaos Louros et al.

NUCLEIC ACIDS RESEARCH (2020)

Article Biochemistry & Molecular Biology

Deep mutational scanning reveals the structural basis for α-synuclein activity

Robert W. Newberry et al.

NATURE CHEMICAL BIOLOGY (2020)

Article Chemistry, Physical

Rosetta Machine Learning Models Accurately Classify Positional Effects of Thioamides on Proteolysis

Sam Giannakoulias et al.

JOURNAL OF PHYSICAL CHEMISTRY B (2020)

Article Chemistry, Multidisciplinary

Rosetta custom score functions accurately predict ΔΔGof mutations at protein-protein interfaces using machine learning

Sumant R. Shringari et al.

CHEMICAL COMMUNICATIONS (2020)

Article Biotechnology & Applied Microbiology

Dimensionality reduction for visualizing single-cell data using UMAP

Etienne Becht et al.

NATURE BIOTECHNOLOGY (2019)

Review Biochemistry & Molecular Biology

Immunogenicity in Protein and Peptide Based-Therapeutics: An Overview

L. Fernandez et al.

CURRENT PROTEIN & PEPTIDE SCIENCE (2018)

Review Computer Science, Artificial Intelligence

Recent Trends in Deep Learning Based Natural Language Processing

Tom Young et al.

IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE (2018)

Article Biology

Factors affecting the physical stability (aggregation) of peptide therapeutics

Karolina L. Zapadka et al.

INTERFACE FOCUS (2017)

Review Cell Biology

GPCR-Mediated Signaling of Metabolites

Anna Sofie Husted et al.

CELL METABOLISM (2017)

Article Biochemistry & Molecular Biology

TANGO-Inspired Design of Anti-Amyloid Cyclic Peptides

Xiaomeng Lu et al.

ACS CHEMICAL NEUROSCIENCE (2016)

Article Biochemistry & Molecular Biology

PASTA 2.0: an improved server for protein aggregation prediction

Ian Walsh et al.

NUCLEIC ACIDS RESEARCH (2014)

Review Computer Science, Artificial Intelligence

Pattern classification and clustering: A review of partially supervised learning approaches

Friedhelm Schwenker et al.

PATTERN RECOGNITION LETTERS (2014)

Article Multidisciplinary Sciences

MetAmyl: A METa-Predictor for AMYLoid Proteins

Mathieu Emily et al.

PLOS ONE (2013)

Review Pharmacology & Pharmacy

Cell-penetrating peptides: classes, origin, and current landscape

Francesca Milletti

DRUG DISCOVERY TODAY (2012)

Editorial Material Biochemical Research Methods

Waltz, an exciting new move in amyloid prediction

Mikael Oliveberg

NATURE METHODS (2010)

Article Biotechnology & Applied Microbiology

Development trends for human monoclonal antibody therapeutics

Aaron L. Nelson et al.

NATURE REVIEWS DRUG DISCOVERY (2010)

Article Biochemistry & Molecular Biology

Prediction of aggregation-prone regions in structured proteins

Gian Gaetano Tartaglia et al.

JOURNAL OF MOLECULAR BIOLOGY (2008)

Article Biochemical Research Methods

UniRef: comprehensive and non-redundant UniProt reference clusters

Baris E. Suzek et al.

BIOINFORMATICS (2007)

Article Biochemical Research Methods

AGGRESCAN:: a server for the prediction and evaluation of hot spots of aggregation in polypeptides

Oscar Conchillo-Sole et al.

BMC BIOINFORMATICS (2007)

Article Multidisciplinary Sciences

Sequence determinants of amyloid fibril formation

ML de la Paz et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2004)

Review Chemistry, Medicinal

Pharmacokinetic aspects of biotechnology products

L Tang et al.

JOURNAL OF PHARMACEUTICAL SCIENCES (2004)

Article Biochemical Research Methods

Beware of q(2)!

A Golbraikh et al.

JOURNAL OF MOLECULAR GRAPHICS & MODELLING (2002)