Curriculum Vitae

(As of April 1st, 2024)

PDF version

Daniel Evans-Yamamoto, Ph.D.

Adjunct Scientist
The Systems Biology Institute

Personal E-mail: dan.yamamoto.evans /at/ gmail.com (Please replace /at/ with @)

Education

Systems Biology program, Graduate school of Media and Governance, Keio University (Japan), 2018 - 2024
Department of Environment and Information Studies, Keio University (Japan), 2014 - 2018, Bachelor degree with Honors

Positions

Current

Researcher, The Systems Biology Institute, April 2024- Current

Former

Adjunct Researcher, The Systems Biology Institute, November 2023- March 2024
Part-time researcher, The Systems Biology Institute, January 2019- October 2023

Research intern, Landry lab, IBIS, Laval University (Canada), December 2020 - September 2023
Research student, Yachie lab, RCAST, The University of Tokyo (Japan), 2014 - 2020
Intern, Landry lab, IBIS, Laval University (Canada), 2018 Aug - 2018 Sep
Member, Robotic biology consortium, 2015 - 2017
Research student, Japan Agency for Marine-Earth Science and Technology (Japan), 2015-2016

Honors and Awards

Awards

  • Outstanding Doctoral Dissertation
    Awarded for the dissertation “Charactrizing protein evolution with systematic protein-protein interaction screenings” by the Systems biology project, Keio University SFC (March 2024)

  • Best poster presentation (PhD and post-doctral devision)
    Awarded for the poster “Barcode Fusion Genetics-Protein-fragment Complementation Assay (BFG-PCA): 
tools and resources that expands the potential for binary protein interaction discovery” presented at IBIS student day 2021

  • Excellent Graduation Project
    Awarded for the graduation thesis “Development of high-throughput technologies to screen protein interactomes” by Keio University (Year of 2018)

Fellowships

  • Research Fellowship for Young Scientist (DC1), JSPS (April 2020 - September 2023, 200 000 JPY/month)
  • Watanabe Foundation International Scholarship, The Watanabe Foundation (June 2022 - February 2023, 150 000 JPY/month)
  • Graduate Fellowship for Young Leaders, Sylff organization through Keio University (2020, 1 000 000 JPY)
  • Tsuruoka Town Campus of Keio Fellowship, Keio University
    (April 2023–March 2024) 1 560 000 JPY
    (April 2022–March 2023) 1 560 000 JPY
    (April 2021–March 2022) 1 560 000 JPY
    (April 2020–March 2021) 1 230 000 JPY
    (April 2019–March 2020) 800 000 JPY
    (April 2018–March 2019) 291 200 JPY
    (April 2017–March 2018) 460 000 JPY
    (April 2016–March 2017) 433 330 JPY
    (April 2015–March 2016) 454 900 JPY

Competetive Research Funds

  1. April 2020–March 2023, Grant-in-Aid for JSPS Fellows, Japan Society for Promotion of Science
    Development of a novel analysis pipeline on protein evolution based on biophysical functionality
    2,500,000 JPY

  2. April 2019–March 2020, Taikichiro Mori Memorial Research Grant, Taikichiro Mori Memorial Research Fund
    Evolution analysis on proteins from biophysical interaction properties
    240,000 JPY

  3. June 2017-February 2018, Yamagishi Student Project Support Program
    Evolutionary analysis of protein complexes from an inter-species screening approach
    240,000 JPY

  4. June 2016-February 2017, Yamagishi Student Project Support Program
    Expanding high-throughput protein interaction detection methods towards personal interactome technologies
    270,000 JPY

Skills

Molecular biology lab techniques

1- Genetic engineering

a. Design and construction of various plasmid DNAs for bacteria, yeast and mammalian cells
b. Design and construction of various gene induction circuits with DNA recombination
c. Design and construction of plasmid DNA libraries including ORFeome libraries and DNA barcodes

2- Yeast molecular biology and genetics

a. Yeast cell culture and transformation
b. In-yeast DNA assembly
c. Protein interaction screening using Yeast two-hybrid and DHFR-PCA methods

3- Mammalian culture cell engineering (moderate)

a. Cell culture and passage of mammalian cells
b. Plasmid DNA transfection of mammalian cells
c. CRISPR/Cas9 base editing in mammalian cells
d. Single-cell transcriptome using Drop-seq system

4- Computational skills

a. Python

  • Data analysis on public data
  • Analyzing high-throughput DNA sequencing data
  • Parallel computing on Sun Grid Engine servers

b. R
- Statistical testing
- Data visualization

c. Genome editing outcome analyses
d. Single-cell transcriptome data analysis using Drop-seq tools (Moderate)
e. Single-cell transcriptome data analysis using R, Seurat package (Moderate)

5- Other skills

a. Operation of a high-throughput sequencer (Illumina MiSeq)
b. Operation of a Nanopore sequencer (Oxford Nanopore Technologies, MinION)

Language(s)

  • Japanese (Mother tongue)
  • English (Father tongue)