Kit-Kay Mak

Computational Theory and Mathematics · 2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kit-Kay Mak trusts overall

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

  1. Hongming Chen
  2. Gisbert Schneider
  3. Marwin H. S. Segler
  4. Ola Engkvist
  5. Polina Mamoshina
  6. Jae Yong Ryu

Who trusts Kit-Kay Mak overall

  1. S. Latif
  2. Maria Batool

Papers from Kit-Kay Mak's perspective

Ordered by how strongly the researchers Kit-Kay Mak trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks
  2. Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data
  3. druGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico. (Molecular Pharmaceutics)
  4. Applications of Deep Learning in Biomedicine.
  5. Can the pharmaceutical industry reduce attrition rates?
  6. DeepTox: Toxicity Prediction using Deep Learning
  7. Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties
  8. Planning chemical syntheses with deep neural networks and symbolic AI
  9. The rise of deep learning in drug discovery. (Drug Discovery Today)
  10. Automating drug discovery (Nature reviews. Drug discovery)

Their papers