Dergi makalesi Açık Erişim

MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery

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


MARC21 XML

<?xml version='1.0' encoding='UTF-8'?>
<record xmlns="http://www.loc.gov/MARC21/slim">
  <leader>00000nam##2200000uu#4500</leader>
  <datafield tag="245" ind1=" " ind2=" ">
    <subfield code="a">MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery</subfield>
  </datafield>
  <datafield tag="909" ind1="C" ind2="4">
    <subfield code="p">BIOINFORMATICS</subfield>
    <subfield code="v">37</subfield>
    <subfield code="n">5</subfield>
    <subfield code="c">693-704</subfield>
  </datafield>
  <controlfield tag="001">237606</controlfield>
  <datafield tag="980" ind1=" " ind2=" ">
    <subfield code="a">user-tubitak-destekli-proje-yayinlari</subfield>
  </datafield>
  <datafield tag="520" ind1=" " ind2=" ">
    <subfield code="a">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.</subfield>
  </datafield>
  <datafield tag="650" ind1="1" ind2="7">
    <subfield code="2">opendefinition.org</subfield>
    <subfield code="a">cc-by</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Atalay, R. Cetin</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Middle East Tech Univ, Grad Sch Informat, Ankara, Turkey</subfield>
    <subfield code="a">Kahraman, D. Cansen</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">Dogan, T.</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">European Bioinformat Inst EMBL EBI, European Mol Biol Lab, Cambridge, Hinxton, England</subfield>
    <subfield code="a">Martin, M.</subfield>
  </datafield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="u">Middle East Tech Univ, Dept Comp Engn, Ankara, Turkey</subfield>
    <subfield code="a">Atalay, V</subfield>
  </datafield>
  <datafield tag="980" ind1=" " ind2=" ">
    <subfield code="b">article</subfield>
    <subfield code="a">publication</subfield>
  </datafield>
  <datafield tag="542" ind1=" " ind2=" ">
    <subfield code="l">open</subfield>
  </datafield>
  <datafield tag="100" ind1=" " ind2=" ">
    <subfield code="a">Rifaioglu, A. S.</subfield>
  </datafield>
  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="c">2021-01-01</subfield>
  </datafield>
  <controlfield tag="005">20221007095917.0</controlfield>
  <datafield tag="909" ind1="C" ind2="O">
    <subfield code="o">oai:aperta.ulakbim.gov.tr:237606</subfield>
    <subfield code="p">user-tubitak-destekli-proje-yayinlari</subfield>
  </datafield>
  <datafield tag="856" ind1="4" ind2=" ">
    <subfield code="z">md5:9b00d9d0bcfc8d80a68f488fe510ec5a</subfield>
    <subfield code="s">238</subfield>
    <subfield code="u">https://aperta.ulakbim.gov.trrecord/237606/files/bib-b16a52b3-b797-40ef-856f-5a874a54cc08.txt</subfield>
  </datafield>
  <datafield tag="540" ind1=" " ind2=" ">
    <subfield code="u">http://www.opendefinition.org/licenses/cc-by</subfield>
    <subfield code="a">Creative Commons Attribution</subfield>
  </datafield>
  <datafield tag="024" ind1=" " ind2=" ">
    <subfield code="a">10.1093/bioinformatics/btaa858</subfield>
    <subfield code="2">doi</subfield>
  </datafield>
</record>
21
10
görüntülenme
indirilme
Görüntülenme 21
İndirme 10
Veri hacmi 2.4 kB
Tekil görüntülenme 18
Tekil indirme 10

Alıntı yap