Dana-Farber repository for machine learning in immunology.
about
Cancer vaccines: state of the art of the computational modeling approachesBioinformatics for cancer immunology and immunotherapyTEPITOPEpan: extending TEPITOPE for peptide binding prediction covering over 700 HLA-DR moleculesPREDIVAC: CD4+ T-cell epitope prediction for vaccine design that covers 95% of HLA class II DR protein diversity.Characterization of the immunophenotypes and antigenomes of colorectal cancers reveals distinct tumor escape mechanisms and novel targets for immunotherapy.The utility and limitations of current Web-available algorithms to predict peptides recognized by CD4 T cells in response to pathogen infectionImmunoinformatics and epitope prediction in the age of genomic medicine.Computational genomics tools for dissecting tumour-immune cell interactions.Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks.InCoB2012 Conference: from biological data to knowledge to technological breakthroughs.Breast cancer vaccination comes to age: impacts of bioinformatics
P2860
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P2860
Dana-Farber repository for machine learning in immunology.
description
2011 nî lūn-bûn
@nan
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
2011年论文
@zh
2011年论文
@zh-cn
name
Dana-Farber repository for machine learning in immunology.
@en
type
label
Dana-Farber repository for machine learning in immunology.
@en
prefLabel
Dana-Farber repository for machine learning in immunology.
@en
P2093
P2860
P1476
Dana-Farber repository for machine learning in immunology.
@en
P2093
Derin B Keskin
Ellis L Reinherz
Guang Lan Zhang
P2860
P356
10.1016/J.JIM.2011.07.007
P577
2011-07-18T00:00:00Z