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HIV Antibodies

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Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.

PLoS computational biology
The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector ce...

Unsupervised selection of RV144 HIV vaccine-induced antibody features correlated to natural killer cell-mediated cytotoxic reactions.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
HIV-1 vaccine injection has been shown less effective due to the diversity of antigens. Increasing the knowledge of the associations between immune system and virus would ultimately result in producing effective vaccines against HIV-1 virus. To incre...

Robotic selection for the rapid development of stable CHO cell lines for HIV vaccine production.

PloS one
The production of envelope glycoproteins (Envs) for use as HIV vaccines is challenging. The yield of Envs expressed in stable Chinese Hamster Ovary (CHO) cell lines is typically 10-100 fold lower than other glycoproteins of pharmaceutical interest. M...

Accurate Prediction for Antibody Resistance of Clinical HIV-1 Isolates.

Scientific reports
Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have promising utility in prevention and treatment of HIV-1 infection, and several are currently undergoing clinical trials. Due to the high sequence diversity an...

Prediction of Contact Residues in Anti-HIV Neutralizing Antibody by Deep Learning.

Japanese journal of infectious diseases
The monoclonal antibody 1C10 targets the V3 loop of HIV-1 and neutralizes a broad range of clade B viruses. However, the mode of interaction between 1C10 and the V3 loop remains unclear because crystallization of 1C10 and the V3 peptide was unsuccess...

Prediction of HIV sensitivity to monoclonal antibodies using aminoacid sequences and deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Knowing the sensitivity of a viral strain versus a monoclonal antibody is of interest for HIV vaccine development and therapy. The HIV strains vary in their resistance to antibodies, and the accurate prediction of virus-antibody sensitivi...

RAIN: machine learning-based identification for HIV-1 bNAbs.

Nature communications
Broadly neutralizing antibodies (bNAbs) are promising candidates for the treatment and prevention of HIV-1 infections. Despite their critical importance, automatic detection of HIV-1 bNAbs from immune repertoires is still lacking. Here, we develop a ...

Learning patterns of HIV-1 resistance to broadly neutralizing antibodies with reduced subtype bias using multi-task learning.

PLoS computational biology
The ability to predict HIV-1 resistance to broadly neutralizing antibodies (bnAbs) will increase bnAb therapeutic benefits. Machine learning is a powerful approach for such prediction. One challenge is that some HIV-1 subtypes in currently available ...