Quang H. Trinh

Nhà nghiên cứu Hồ sơ 6/10

12 công bố · 192 trích dẫn · h-index 7

Thông tin

🏛️Nơi công tác: Đại học Bách khoa Hà Nội
🔬Lĩnh vực: Sinh học
🆔ORCID: 0000-0001-9724-8405
✍️Hồ sơ chưa đầy đủ — bổ sung thông tin

Chỉ số h-index 7 xếp học giả này vào lĩnh vực Sinh học, thuộc nhóm 25% dẫn đầu trong 3.752 hồ sơ cùng lĩnh vực của danh bạ này.

Công bố tiêu biểu

iCYP-MFE: Identifying Human Cytochrome P450 Inhibitors Using Multitask Learning and Molecular Fingerprint-Embedded Encoding47 trích dẫn
Journal of Chemical Information and Modeling · 2021 · DOI

iANP-EC: Identifying Anticancer Natural Products Using Ensemble Learning Incorporated with Evolutionary Computation40 trích dẫn
Journal of Chemical Information and Modeling · 2022 · DOI

Predicting Antimalarial Activity in Natural Products Using Pretrained Bidirectional Encoder Representations from Transformers29 trích dẫn
Journal of Chemical Information and Modeling · 2021 · DOI

From SMILES to Enhanced Molecular Property Prediction: A Unified Multimodal Framework with Predicted 3D Conformers and Contrastive Learning Techniques20 trích dẫn
Journal of Chemical Information and Modeling · 2024 · DOI

iPromoter-Seqvec: identifying promoters using bidirectional long short-term memory and sequence-embedded features18 trích dẫn
BMC Genomics · 2022 · DOI

Predicting Cardiotoxicity of Molecules Using Attention-Based Graph Neural Networks17 trích dẫn
Journal of Chemical Information and Modeling · 2024 · DOI

i4mC-GRU: Identifying DNA N 4 -Methylcytosine sites in mouse genomes using bidirectional gated recurrent unit and sequence-embedded features13 trích dẫn
Computational and Structural Biotechnology Journal · 2023 · DOI

iNSP‐GCAAP: Identifying nonclassical secreted proteins using global composition of amino acid properties5 trích dẫn
PROTEOMICS · 2022 · DOI

iR1mA-LSTM: Identifying N$$^{1}$$-Methyladenosine Sites in Human Transcriptomes Using Attention-Based Bidirectional Long Short-Term Memory2 trích dẫn
Studies in computational intelligence · 2023 · DOI

iR6mA-RNN: Identifying N6-Methyladenosine Sites in Eukaryotic Transcriptomes using Recurrent Neural Networks and Sequence-embedded Features1 trích dẫn
· 2023 · DOI

Về lĩnh vực Sinh học

3.752học giả

51.546công bố

942.318trích dẫn

4.1h-index trung bình

Hướng nghiên cứu phổ biến trong lĩnh vực:

Genomics and Phylogenetic StudiesPlant-Microbe Interactions and ImmunityPlant tissue culture and regenerationPlant Diversity and EvolutionPlant and animal studiesPlant and Fungal Species Descriptions

Nơi có nhiều học giả lĩnh vực này nhất: