AIMC Topic: Membrane Proteins

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Analyzing protein dynamics from fluorescence intensity traces using unsupervised deep learning network.

Communications biology Nov 12, 2020
We propose an unsupervised deep learning network to analyze the dynamics of membrane proteins from the fluorescence intensity traces. This system was trained in an unsupervised manner with the raw experimental time traces and synthesized ones, so nei...
Humans Deep Learning Membrane Proteins Microscopy, Fluorescence Diffusion HeLa Cells Carbocyanines Unsupervised Machine Learning MCF-7 Cells Fluorescent Dyes
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Ensemble learning models that predict surface protein abundance from single-cell multimodal omics data.

Methods (San Diego, Calif.) Oct 9, 2020
Single-cell protein abundance is a fundamental type of information to characterize cell states. Due to high cost and technical barriers, however, direct quantification of proteins is difficult. Single-cell RNA sequencing (scRNA-seq) data, serving as ...
Sequence Analysis, RNA Membrane Proteins Gene Expression Regulation Humans Single-Cell Analysis Transcriptome Computational Biology Deep Learning
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DEEPSMP: A deep learning model for predicting the ectodomain shedding events of membrane proteins.

Journal of bioinformatics and computational biology Jun 23, 2020
Membrane proteins play essential roles in modern medicine. In recent studies, some membrane proteins involved in ectodomain shedding events have been reported as the potential drug targets and biomarkers of some serious diseases. However, there are f...
Neural Networks, Computer Models, Molecular Protein Domains Membrane Proteins Databases, Protein Area Under Curve Reproducibility of Results Sensitivity and Specificity Deep Learning
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IMPContact: An Interhelical Residue Contact Prediction Method.

BioMed research international Mar 25, 2020
As an important category of proteins, alpha-helix transmembrane proteins (TMPs) play an important role in various biological activities. Because the solved αTMP structures are inadequate, predicting the residue contacts among the transmembrane segmen...
Machine Learning Neural Networks, Computer Algorithms Computational Biology Protein Conformation Membrane Proteins Databases, Protein
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Computational Identification and Analysis of Ubiquinone-Binding Proteins.

Cells Feb 24, 2020
Ubiquinone is an important cofactor that plays vital and diverse roles in many biological processes. Ubiquinone-binding proteins (UBPs) are receptor proteins that dock with ubiquinones. Analyzing and identifying UBPs via a computational approach will...
Membrane Proteins Carrier Proteins Amino Acid Sequence Machine Learning Protein Binding Computational Biology Sequence Analysis, Protein Protein Interaction Domains and Motifs Position-Specific Scoring Matrices Ubiquinone Gene Ontology Binding Sites Humans
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Accurate classification of membrane protein types based on sequence and evolutionary information using deep learning.

BMC bioinformatics Dec 24, 2019
BACKGROUND: Membrane proteins play an important role in the life activities of organisms. Knowing membrane protein types provides clues for understanding the structure and function of proteins. Though various computational methods for predicting memb...
Membrane Proteins Sequence Analysis Deep Learning Computational Biology
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Propofol affects the growth and metastasis of pancreatic cancer via ADAM8.

Pharmacological reports : PR Dec 20, 2019
BACKGROUND: Anesthesia is a major component of surgery and recently considered an important regulator of cell phenotypes. Here we aimed to investigate propofol, an anesthesia drug, in suppressing pancreatic cancer (PDAC), focusing on A disintegrin an...
ADAM Proteins Propofol Mice, SCID Cell Movement Xenograft Model Antitumor Assays Apoptosis Cell Line, Tumor Matrix Metalloproteinase 9 Neoplasm Metastasis Neoplasm Invasiveness Membrane Proteins Matrix Metalloproteinase 2 Pancreatic Neoplasms Cell Proliferation MAP Kinase Signaling System Humans Animals Antineoplastic Agents
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A 21‑gene Support Vector Machine classifier and a 10‑gene risk score system constructed for patients with gastric cancer.

Molecular medicine reports Nov 21, 2019
Gastric cancer (GC) ranks fifth in terms of incidence and third in terms of tumor mortality worldwide. The present study was designed to construct a Support Vector Machine (SVM) classifier and risk score system for GC. The GSE62254 (training set) and...
Angiopoietin-Like Protein 1 Prognosis Female Risk Factors Humans Carrier Proteins Male Cytokines Middle Aged Nerve Tissue Proteins Aged Neoplasm Recurrence, Local Membrane Proteins Gene Expression Profiling Stomach Neoplasms Angiopoietin-like Proteins Support Vector Machine Gene Regulatory Networks Tumor Suppressor Proteins A Kinase Anchor Proteins Databases, Genetic Gene Expression Regulation, Neoplastic Kaplan-Meier Estimate
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Distance-based protein folding powered by deep learning.

Proceedings of the National Academy of Sciences of the United States of America Aug 9, 2019
Direct coupling analysis (DCA) for protein folding has made very good progress, but it is not effective for proteins that lack many sequence homologs, even coupled with time-consuming conformation sampling with fragments. We show that we can accurate...
Sequence Alignment Membrane Proteins Models, Molecular Protein Folding Algorithms Deep Learning Time Factors
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Efficient utilization on PSSM combining with recurrent neural network for membrane protein types prediction.

Computational biology and chemistry Aug 8, 2019
Position-Specific Scoring Matrix (PSSM) is an excellent feature extraction method that was proposed early in protein classifying prediction, but within the restriction of feature shape in PSSM, researchers make a lot attempts to process it so that PS...
Position-Specific Scoring Matrices Neural Networks, Computer Computational Biology Membrane Proteins Databases, Protein
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