Fuqiang Ban

Computational Theory and Mathematics · 2017–2022

A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Fuqiang Ban trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Jerome H. Friedman
  2. Nicolai Meinshausen
  3. Yoshihiro Yamanishi
  4. Kevin Bleakley

Papers from Fuqiang Ban's perspective

Ordered by how strongly the researchers Fuqiang Ban trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Prediction of drug–target interaction networks from the integration of chemical and genomic spaces (Intelligent Systems in Molecular Biology)
  2. Greedy function approximation: A gradient boosting machine.
  3. Gaussian interaction profile kernels for predicting drug-target interaction (Bioinform.)
  4. Supervised prediction of drug–target interactions using bipartite local models (Bioinform.)
  5. Drug Target Identification Using Side-Effect Similarity
  6. XGBoost: A Scalable Tree Boosting System
  7. A fast flexible docking method using an incremental construction algorithm.
  8. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility
  9. Matrix Factorization Techniques for Recommender Systems
  10. Protein-ligand interaction prediction: an improved chemogenomics approach (Bioinform.)

Their papers