The recent boom in single-cell omics has brought researchers one step closer to
understanding the biological mechanisms associated with cell heterogeneity. Rare
cells that have historically been obscured by bulk measurement techniques are
being studied by single cell analysis and providing valuable insight into cell
function. To support this progress, novel upstream capabilities are required for
single cell preparation for analysis. Presented here is a droplet microfluidic,
image-based single-cell sorting technique that is flexible and programmable. The
automated system performs real-time dualcamera imaging (brightfield &
fluorescent), processing, decision making and sorting verification. To demonstrate
capabilities, the system was used to overcome the Poisson loading problem by
sorting for droplets containing a single red blood cell with 85% purity.
Furthermore, fluorescent imaging and machine learning was used to load single
K562 cells amongst clusters based on their instantaneous size and circularity. The
presented system aspires to replace manual cell handling techniques by translating
expert knowledge into cell sorting automation via machine learning algorithms.
This powerful technique finds application in the enrichment of single cells based on
their micrographs for further downstream processing and analysis.

제 1편 : MATLAB 기본편
1. MATLAB 기본사용편 ···················· 003
1.1 MATLAB 시작하기 ·························· 003
명령창(command Window)에서의 입력 005
도움말(Help)의 이용 ······························· 007
1.2 입력 오류의 수정 ····························· 008
계산의 중지 ·············································· 009
MATLAB 종료하기 ································· 009
1.3 연산과 변수의 할당 ·························· 009
연산자 우선순위 ······································· 011
내장함수 ···················································· 012
1.4 데이터의 표현 ··································· 013
1.5 변수의 처리 ······································· 015
변수 이름 ·················································· 015
clear 명령어 ············································· 016
특수변수와 정수 ······································· 017
whos 명령어 ············································ 017
1.6 벡터와 행렬 ······································· 018
벡터 ··························································· 018
행렬 ·························································· 023
스크린 출력과 억제 ································· 024
1.7 랜덤(Random)수와 복소수 ·············· 025
랜덤 수 ····················································· 025
복소수 ······················································· 027
1.8 기호를 이용한 연산 ·························· 028
기호식에서의 치환 ··································· 029
1.9 코드 파일 ·········································· 030
스크립트 코드 파일 ································· 030
코멘트의 추가 ·········································· 032
함수 코드 파일 ···································· 033
사용자 정의함수 ······································ 036
1.10 간단한 그래프의 생성 ····················· 037
ezplot을 이용한 그래프 ·························· 037
plot을 이용한 그래프 ·························· 039
3차원 그래프 ··········································· 042
1.11 MATLAB과 엑셀(Excel)의 접속 043 엑셀 데이터 불러오기 ····························· 043
데이터 가져오기 옵션 ························· 046
스크립트 생성 옵션 ································· 049
함수 생성 옵션 ········································ 049
생성된 데이터를 엑셀파일로 저장하기 ·· 050

제 2편 : 연구논문
Image-Based Single Cell Sorting Automation in Droplet Microfluidics

1. System Overview 52
2. Results & Discussion 56
3. Conclusion 59
4. Materials & Methods 60
5. Data availability 61
6. References 62