Generation and analyses of human synthetic antibody libraries and their application for protein microarrays.

By Anna Säll, Mary Walle, C. Wingren, S. Müller, T. Nyman, A. Vala, Mats Ohlin, C. Borrebaeck, H. Persson. 2016

40 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Molecular Biology, Radiology, Nuclear Medicine and Imaging

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Debora Marks
2. Christopher Sander
3. Adam J. Riesselman
4. Jung-Eun Shin
5. A. Kruse
6. Conor McMahon
7. A. Manglik
8. Elana Simon

In Radiology, Nuclear Medicine and Imaging

1. Adam J. Riesselman
2. Christopher Sander
3. Jung-Eun Shin
4. Aaron W. Kollasch
5. Elana Simon
6. A. Manglik
7. Debora Marks
8. A. Kruse

Citations in the corpus

• Accelerating Protein Design Using Autoregressive Generative Models (2019, background): “Recently, phage and yeast display methods have allowed for high-throughput screening of libraries of antibodies and nanobodies (S¨all et al., 2016; McMahon et al., 2018).”
• Protein design and variant prediction using autoregressive generative models (2021, background): “Three additional insertion and deletion mutation scan fi tness predictions are included in the supplement: yeast snoRNA ( ρ = 0.49; Supplementary Data 4), beta-lactamase ( ρ = 0.45; Supplementary Data 5), and p53 ( ρ = 0.035; Supplementary Data 6) (see Supplementary Fig.”