1 Ocak 2021 Dergi makalesi Açık Erişim

Rifaioglu, A. S.; Atalay, R. Cetin; Kahraman, D. Cansen; Dogan, T.; Martin, M.; Atalay, V

Citation Style Language JSON

{
  "DOI": "10.1093/bioinformatics/btaa858", 
  "abstract": "Motivation: Identification of interactions between bioactive small molecules and target proteins is crucial for novel drug discovery, drug repurposing and uncovering off-target effects. Due to the tremendous size of the chemical space, experimental bioactivity screening efforts require the aid of computational approaches. Although deep learning models have been successful in predicting bioactive compounds, effective and comprehensive featurization of proteins, to be given as input to deep neural networks, remains a challenge.", 
  "author": [
    {
      "family": "Rifaioglu", 
      "given": " A. S."
    }, 
    {
      "family": "Atalay", 
      "given": " R. Cetin"
    }, 
    {
      "family": "Kahraman", 
      "given": " D. Cansen"
    }, 
    {
      "family": "Dogan", 
      "given": " T."
    }, 
    {
      "family": "Martin", 
      "given": " M."
    }, 
    {
      "family": "Atalay", 
      "given": " V"
    }
  ], 
  "container_title": "BIOINFORMATICS", 
  "id": "237606", 
  "issue": "5", 
  "issued": {
    "date-parts": [
      [
        2021, 
        1, 
        1
      ]
    ]
  }, 
  "page": "693-704", 
  "title": "MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery", 
  "type": "article-journal", 
  "volume": "37"
}