Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets

Original language	American English
Media of output	Departmental Seminar/Colloquium
Place of Publication	Ben Gurion University; Faculty of Engineering
State	Published - 2012

Activities

• 4 Oral presentation

Activities per year

• Departmental Seminar/Colloquium: Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets

  Yaari, G. (Speaker)

  2012 → …

  Activity: Talk or presentation › Oral presentation

• Departmental Seminar/Colloquium: Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets

  Yaari, G. (Speaker)

  2012 → …

  Activity: Talk or presentation › Oral presentation

• Departmental Seminar/Colloquium: Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets

  Yaari, G. (Speaker)

  2012 → …

  Activity: Talk or presentation › Oral presentation

View all 4 activities

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Yaari, G. (2012). Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets.

Yaari, Gur. / Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets. 2012. Ben Gurion University; Faculty of Engineering.

@misc{8b35c4f8c9eb4b6481d63913dfaa449a,

title = "Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets",

author = "Gur Yaari",

year = "2012",

language = "American English",

type = "Other",

}

Yaari, G 2012, Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets. Ben Gurion University; Faculty of Engineering.

Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets. / Yaari, Gur.
Ben Gurion University; Faculty of Engineering. 2012.

Research output: Other contribution › peer-review

TY - GEN

T1 - Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets

AU - Yaari, Gur

PY - 2012

Y1 - 2012

M3 - Other contribution

CY - Ben Gurion University; Faculty of Engineering

ER -

Yaari G. Bayesian approach for quantifying selection in high-throughput antibody sequencing datasets. 2012.