AI Medical Compendium Topic:
Amino Acid Sequence

Clear Filters Showing 381 to 390 of 664 articles

AGONOTES: A Robot Annotator for Argonaute Proteins.

Interdisciplinary sciences, computational life sciences
The argonaute protein (Ago) exists in almost all organisms. In eukaryotes, it functions as a regulatory system for gene expression. In prokaryotes, it is a type of defense system against foreign invasive genomes. The Ago system has been engineered fo...

An improved deep learning method for predicting DNA-binding proteins based on contextual features in amino acid sequences.

PloS one
As the number of known proteins has expanded, how to accurately identify DNA binding proteins has become a significant biological challenge. At present, various computational methods have been proposed to recognize DNA-binding proteins from only amin...

SDBP-Pred: Prediction of single-stranded and double-stranded DNA-binding proteins by extending consensus sequence and K-segmentation strategies into PSSM.

Analytical biochemistry
Identification of DNA-binding proteins (DNA-BPs) is a hot issue in protein science due to its key role in various biological processes. These processes are highly concerned with DNA-binding protein types. DNA-BPs are classified into single-stranded D...

Unified rational protein engineering with sequence-based deep representation learning.

Nature methods
Rational protein engineering requires a holistic understanding of protein function. Here, we apply deep learning to unlabeled amino-acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically...

Computational methods and tools for binding site recognition between proteins and small molecules: from classical geometrical approaches to modern machine learning strategies.

Journal of computer-aided molecular design
In the current "genomic era" the number of identified genes is growing exponentially. However, the biological function of a large number of the corresponding proteins is still unknown. Recognition of small molecule ligands (e.g., substrates, inhibito...

Uncovering Thousands of New Peptides with Sequence-Mask-Search Hybrid Peptide Sequencing Framework.

Molecular & cellular proteomics : MCP
Typical analyses of mass spectrometry data only identify amino acid sequences that exist in reference databases. This restricts the possibility of discovering new peptides such as those that contain uncharacterized mutations or originate from unexpec...

One-shot optimization of multiple enzyme parameters: Tailoring glucose oxidase for pH and electron mediators.

Biotechnology and bioengineering
Enzymes are biological catalysts with many industrial applications, but natural enzymes are usually unsuitable for industrial processes because they are not optimized for the process conditions. The properties of enzymes can be improved by directed e...

econvRBP: Improved ensemble convolutional neural networks for RNA binding protein prediction directly from sequence.

Methods (San Diego, Calif.)
RNA binding proteins (RBPs) determine RNA process from synthesis to decay, which play a key role in RNA transport, translation and degradation. Therefore, exploring RBPs' function from the amino acid sequence using computational methods has become on...

Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning.

International journal of molecular sciences
In this work, we improved a previous model used for the prediction of proteomes as new B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its sequence, a known reference epitope sequence under specific ...

Sequence assignment for low-resolution modelling of protein crystal structures.

Acta crystallographica. Section D, Structural biology
The performance of automated model building in crystal structure determination usually decreases with the resolution of the experimental data, and may result in fragmented models and incorrect side-chain assignment. Presented here are new methods for...