Jianfeng Sun
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  • Posts
    • A unified ecosystem established to integrate UMI-centric analyses for improved molecular quantification accuracy
    • scRNA-seq analysis learning note-1
  • Softwares
  • Softwares
    • Tresor
    • mclUMI
    • UMIche
    • PyPropel
    • PCSER
    • ResimPy
    • TMKit
    • DeepdlncUD
    • Drutai
    • DeepsmirUD
    • DeepTMInter
    • DeepHelicon
  • News
    • 🎉 Publication in Nature Communications (11.03.2025)
    • 🎉 Publication in Communications Biology (16.01.2025)
    • 🎉 Full member of Sigma Xi
    • 🎉 Publication in Nature Methods (Volume 21 Issue 3, March 2024)
  • Publications
    • SVLearn: a dual-reference machine learning approach enables accurate cross-species genotyping of structural variants
    • PyPropel: a Python-based tool for efficiently processing and characterising protein data
    • Enhancing single-cell transcriptomics using interposed anchor oligonucleotide sequences
    • mclUMI: Markov clustering of unique molecular identifiers enables dynamic removal of PCR duplicates
    • Tresor: An integrated platform for simulating transcriptomic reads with realistic PCR error representation across various RNA sequencing technologies
    • UMIche: A platform for robust UMI-centric simulation and analysis in bulk and single-cell sequencing
    • Evaluating Performance of Different RNA Secondary Structure Prediction Programs Using Self-cleaving Ribozymes
    • An Oral Nanomedicine Elicits In Situ Vaccination Effect against Colorectal Cancer
    • Correcting PCR amplification errors in unique molecular identifiers to generate accurate numbers of sequencing molecules
    • PLMC: Language Model of Protein Sequences Enhances Protein Crystallization Prediction
    • Transient Mild Photothermia Improves Therapeutic Performance of Oral Nanomedicines with Enhanced Accumulation in the Colitis Mucosa
    • TMKit: a Python interface for computational analysis of transmembrane proteins
    • Bioinspired Polyacrylic Acid-Based Dressing: Wet Adhesive, Self-Healing, and Multi-Biofunctional Coacervate Hydrogel Accelerates Wound Healing
    • DeepdlncUD: Predicting regulation types of small molecule inhibitors on modulating lncRNA expression by deep learning
    • DeepsmirUD: Prediction of Regulatory Effects on microRNA Expression Mediated by Small Molecules Using Deep Learning
    • Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications
    • Plasma lipidome reveals susceptibility and resistance of Pekin ducks to DHAV-3
    • Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications
    • Tea leaf-derived exosome-like nanotherapeutics retard breast tumor growth by pro-apoptosis and microbiota modulation
    • Unveiling the hidden role of aquatic viruses in hydrocarbon pollution bioremediation
    • Edible plant-derived nanotherapeutics and nanocarriers: recent progress and future directions
    • Oral Nanomotor-Enabled Mucus Traverse and Tumor Penetration for Targeted Chemo-Sono-Immunotherapy against Colon Cancer
    • Oral nanotherapeutics based on Antheraea pernyi silk fibroin for synergistic treatment of ulcerative colitis
    • PSRR: A Web Server for Predicting the Regulation of miRNAs Expression by Small Molecules
    • Complex Age- and Cancer-Related Changes in Human Blood Transcriptome—Implications for Pan-Cancer Diagnostics
    • Genetic hybridization of highly active exogenous functional proteins into silk-based materials using “light-clothing” strategy
    • Improved sequence-based prediction of interaction sites in α-helical transmembrane proteins by deep learning
    • Missense Variant of Endoplasmic Reticulum Region of WFS1 Gene Causes Autosomal Dominant Hearing Loss without Syndromic Phenotype
    • DeepHelicon: Accurate prediction of inter-helical residue contacts in transmembrane proteins by residual neural networks
    • Improving Residue-Residue Contacts Prediction from Protein Sequences Using RNN-Based LSTM Network
    • E-Index for Differentiating Complex Dynamic Traits
  • Projects
    • Direct RNA-seq
    • PROTAC off-target effect prediction
    • Variant effect prediction
  • Teaching
    • Demultiplexing for molecular quantification
    • Machine learning in structural biology
  • Projects
  • Experience
  • Recent & Upcoming Talks
    • Botnar Seminar Series 2023
    • ICMLC 2019
    • PIMRC 2015

DeepTMInter

Mar 9, 2021 · 1 min read
Go to Project Site

DeepTMInter is a deep-learning-based approach for predicting interaction sites in transmembrane proteins. It was developed using stacked generalization ensembles of ultradeep residual neural networks.

Last updated on Mar 9, 2021
Protein Ppi Sequence Analysis Python
Jianfeng Sun
Authors
Jianfeng Sun
Postdoctoral researcher
← DeepsmirUD Jan 18, 2023
DeepHelicon Jul 11, 2020 →

© 2025 Jianfeng Sun. This work is licensed under CC BY NC ND 4.0

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