Notes

기술 노트

129

NGS 분석, 프로그래밍, 통계, 분자생물학 학습 기록

Biology

7. 진핵생물의 전사조절

·분자생물학 #7
Biology

8. 단백질 합성

·분자생물학 #8
Biology

6. 원핵생물의 전사조절

·분자생물학 #6
Biology

4. 돌연변이와 DNA 수선

·분자생물학 #4
Biology

5. 유전자 전사와 RNA 가공

·분자생물학 #5
Biology

1. DNA, RNA, Protein

·분자생물학 #1
Biology

2. DNA 구조와 핵산 기술

·분자생물학 #2
Biology

3. DNA 복제

·분자생물학 #3
ML & Data

ch12. Model Selection

·ML with Python Cookbook #12
ML & Data

ch13. Linear Regression

·ML with Python Cookbook #13
ML & Data

ch14. Tree and Random Forest

·ML with Python Cookbook #14
ML & Data

ch15. K-Nearest Neighbor

·ML with Python Cookbook #15
Programming

Special Sort Algorithm - Counting Sort

·Sort Algorithm
Programming

Special Sort Algorithm - Radix Sort

·Sort Algorithm
Programming

Advanced Sort Algorithm - Heap Sort

·Sort Algorithm
Bioinformatics

Epigenetics VI - 후성유전체 데이터 생산과 분석1

·Epigenetics #6
Bioinformatics

Epigenetics IV- ncRNA에 의한 전사조절

·Epigenetics #4
Bioinformatics

Epigenetics V- 세포운명 결정의 후성유전학

·Epigenetics #5
Bioinformatics

Epigenetics III - 히스톤 변형과 DNA 메틸화

·Epigenetics #3
Bioinformatics

Epigenetics II - 크로마틴 구조

·Epigenetics #2
Bioinformatics

Epigenetics I - 후성유전학의 개요

·Epigenetics #1
Bioinformatics

생물정보학을 위한 R프로그래밍 V - 데이터 시각화

·생물정보학을 위한 R프로그래밍 #5
Bioinformatics

생물정보학을 위한 R프로그래밍 IV - 데이터 취득과 정제

·생물정보학을 위한 R프로그래밍 #4
Bioinformatics

생물정보학을 위한 R프로그래밍 III - 데이터형과 연산

·생물정보학을 위한 R프로그래밍 #3
Bioinformatics

Interpretation Databases

Bioinformatics

Solid Tumors - Hereditary

Bioinformatics

Solid Tumors - Sporadic

Bioinformatics

생물정보학을 위한 R프로그래밍 II - 데이터형과 연산

·생물정보학을 위한 R프로그래밍 #2
Bioinformatics

암 유전체 빅데이터

Bioinformatics

생물정보학을 위한 R프로그래밍 I - R 설치 및 환경설정

·생물정보학을 위한 R프로그래밍 #1
Bioinformatics

Big Data in Precision Oncology - TCGA 데이터베이스의 이해 및 활용

Bioinformatics

AMP Guideline

Bioinformatics

Big Data in Precision Oncology - TCGA 및 암유전체 빅데이터 개요

Bioinformatics

PRS(Polygenic Risk Score)

Programming

Advanced Sort Algorithm - Merge Sort

·Sort Algorithm
Programming

Advanced Sort Algorithm - Quick Sort

·Sort Algorithm
Programming

Sort Algorithm - Bubble Sort

·Sort Algorithm
Programming

Sort Algorithm - Insertion Sort

·Sort Algorithm
Programming

Sort Algorithm - Selection Sort

·Sort Algorithm
Bioinformatics

Long Read Sequencing VI - SV Calling

·Long Read Sequencing #6
Bioinformatics

Long Read Sequencing VII - Visualization

·Long Read Sequencing #7
Bioinformatics

Long Read Sequencing V - Assembly Quality 확인

·Long Read Sequencing #5
Bioinformatics

Long Read Sequencing IV - Repeat/Gene Annotation

·Long Read Sequencing #4
Bioinformatics

Long Read Sequencing II - 유전체 지도 작성 개괄

·Long Read Sequencing #2
Bioinformatics

Long Read Sequencing III - 유전체 크기 추정하기

·Long Read Sequencing #3
Bioinformatics

Long Read Sequencing I - Introduction

·Long Read Sequencing #1
Programming

(Error) CommandNotFoundError - Your shell has not been properly configured to use 'conda activate'

Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 10. Non-Parametric Multiple Comparison with python

·파이썬을 활용한 데이터 분석 (중급) #10
Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 11. Summary

·파이썬을 활용한 데이터 분석 (중급) #11
Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 9. Kruskal-Wallis Rank Sum Test with python

·파이썬을 활용한 데이터 분석 (중급) #9
Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 7. Analysis of Variance with python

·파이썬을 활용한 데이터 분석 (중급) #7
Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 8. Parametric Multiple Comparison with python

·파이썬을 활용한 데이터 분석 (중급) #8
Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 5. Paired t-test with python

·파이썬을 활용한 데이터 분석 (중급) #5
Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 6. Wilcoxon's matched pairs signed rank test with python

·파이썬을 활용한 데이터 분석 (중급) #6
Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 4. Wilcoxons Rank Sum Test with python

·파이썬을 활용한 데이터 분석 (중급) #4
Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 3. Two Sample t-Test with python

·파이썬을 활용한 데이터 분석 (중급) #3
Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 2. Wilcoxon's Signed Rank Test with python

·파이썬을 활용한 데이터 분석 (중급) #2
Bioinformatics

파이썬을 활용한 데이터 분석 (중급) - 1. One Sample t-Test with python

·파이썬을 활용한 데이터 분석 (중급) #1
Bioinformatics

ML and DL for Cancer Genomics VI - 딥러닝 구동 환경 구축 1

·ML and DL for Cancer Genomics #6
Biology

Genetic Testing Agency Training 6 - 검사대상자의 권리

·유전자검사기관 교육
Bioinformatics

ML and DL for Cancer Genomics II - ML Basic Concpts and Evaluation Methods

·ML and DL for Cancer Genomics #2
Bioinformatics

ML and DL for Cancer Genomics III - DL Algorithm I

·ML and DL for Cancer Genomics #3
Bioinformatics

ML and DL for Cancer Genomics IV - DL Algorithm II

·ML and DL for Cancer Genomics #4
Biology

Genetic Testing Agency Training 4 - 유전자검사기관의 의무 및 책임

·유전자검사기관 교육
Biology

Genetic Testing Agency Training 5 - 유전자검사기관의 숙련도 평가

·유전자검사기관 교육
Biology

Genetic Testing Agency Training 3 - 유전자검사항목의 신고

·유전자검사기관 교육
Biology

Genetic Testing Agency Training 1 - 유전자검사의 이해

·유전자검사기관 교육
Biology

Genetic Testing Agency Training 2 - 유전자검사 제도의 이해

·유전자검사기관 교육
Bioinformatics

ML and DL for Cancer Genomics I - Bioinformatics Trend

·ML and DL for Cancer Genomics #1
Programming

(Cheat Sheet) - Matplotlib

Programming

(Cheat Sheet) - Pandas

Programming

(Cheat Sheet) - Seaborn

Bioinformatics

Transcriptome II - Data Preprocessing

·Transcriptome #2
Bioinformatics

Transcriptome III - Differential Expression & Visual Exploration

·Transcriptome #3
Programming

SQL 기초

Programming

Sub-query and JOIN, UNION

Bioinformatics

Transcriptome I - Introduction to Transcriptome

·Transcriptome #1
Programming

Definition of Data

Programming

Relational Model

Bioinformatics

Variants Analysis VI - Cancer Immunotherapy

·Variants Analysis #6
Bioinformatics

Variants Analysis IV

Bioinformatics

Variants Analysis V - Cancer Analysis

·Variants Analysis #5
Bioinformatics

Variants Analysis III

Bioinformatics

Clustering of Single Cell & Cell Type Assignment I

Bioinformatics

Preprocessing of Single Cell Analysis II

Bioinformatics

Preprocessing of Single Cell Analysis I

Bioinformatics

Experimental Design for Single Cell Analysis

Bioinformatics

Introduce to Single Cell Analysis

Bioinformatics

Variants Analysis II

Bioinformatics

Variants Analysis I

Bioinformatics

WES Clinical Interpretaion I

Bioinformatics

WES Clinical Interpretaion II

Bioinformatics

WES Dominant Variants

Bioinformatics

WES Recessive Variants

Bioinformatics

WES Structural Variants

Bioinformatics

WES 데이터 처리와 해석법

Bioinformatics

WES 연구 디자인법

Bioinformatics

WES 개념과 유전학적 의의

Statistics

ch2. Introduce Linear Algebra

·Guide to Linear Algebra #2
Statistics

ch3. Linear Algebra Calculations

·Guide to Linear Algebra #3
Statistics

ch9. Expectation, Indicator Random Variables, Linearity

·Statistics (Harvard Stat110) #9
Statistics

ch8. Random Variables and Their Distributions

·Statistics (Harvard Stat110) #8
Bioinformatics

Sequencing Technologies

Bioinformatics

about DNA

Statistics

ch7. Gambler's Ruin and Random Variables

·Statistics (Harvard Stat110) #7
Statistics

ch6. Monty Hall, Simpson's Paradox

·Statistics (Harvard Stat110) #6
Statistics

ch5. Conditioning Continued, Law of Total Probability

·Statistics (Harvard Stat110) #5
Statistics

ch4. Conditional Probability

·Statistics (Harvard Stat110) #4
Bioinformatics

Phred Score (Base Call Quality Score)

Bioinformatics

Fastq

Statistics

ch3. Birthday Problem, Properties of Probability

·Statistics (Harvard Stat110) #3
Statistics

ch2. Story Proofs, Axioms of Probability

·Statistics (Harvard Stat110) #2
Statistics

ch1. Probability and Counting

·Statistics (Harvard Stat110) #1
Statistics

ch1. Basic Mathmatics

·Guide to Linear Algebra #1
ML & Data

ch11. Evaluation of Model

·ML with Python Cookbook #11
ML & Data

ch10. Dimension Reduction Using Feature Selection

·ML with Python Cookbook #10
ML & Data

ch5. Category Data

·ML with Python Cookbook #5
ML & Data

ch9. Dimension Reduction Using Feature Extraction

·ML with Python Cookbook #9
ML & Data

ch4. Numeric Data

·ML with Python Cookbook #4
Programming

Search Algorithm - BFS (Breadth-First Search)

·Search Algorithm
ML & Data

ch3. Data Wrangling

·ML with Python Cookbook #3
ML & Data

ch1. Vector Matrix Array

·ML with Python Cookbook #1
ML & Data

ch2. Data Load

·ML with Python Cookbook #2
Programming

Dataframe in Pandas

Programming

Stack vs Queue

Programming

Search Algorithm - DFS (Depth-First Search)

·Search Algorithm
Programming

Style Guide for Shell - Google

Programming

Style Guide for Python Code - PEP8

Programming

VS code

Series

ML with Python Cookbook12편
  1. 1ch1. Vector Matrix Array
  2. 2ch2. Data Load
  3. 3ch3. Data Wrangling
  4. 4ch4. Numeric Data
  5. 5ch5. Category Data
  6. 9ch9. Dimension Reduction Using Feature Extraction
  7. 10ch10. Dimension Reduction Using Feature Selection
  8. 11ch11. Evaluation of Model
  9. 12ch12. Model Selection
  10. 13ch13. Linear Regression
  11. 14ch14. Tree and Random Forest
  12. 15ch15. K-Nearest Neighbor
파이썬을 활용한 데이터 분석 (중급)11편
  1. 1파이썬을 활용한 데이터 분석 (중급) - 1. One Sample t-Test with python
  2. 2파이썬을 활용한 데이터 분석 (중급) - 2. Wilcoxon's Signed Rank Test with python
  3. 3파이썬을 활용한 데이터 분석 (중급) - 3. Two Sample t-Test with python
  4. 4파이썬을 활용한 데이터 분석 (중급) - 4. Wilcoxons Rank Sum Test with python
  5. 5파이썬을 활용한 데이터 분석 (중급) - 5. Paired t-test with python
  6. 6파이썬을 활용한 데이터 분석 (중급) - 6. Wilcoxon's matched pairs signed rank test with python
  7. 7파이썬을 활용한 데이터 분석 (중급) - 7. Analysis of Variance with python
  8. 8파이썬을 활용한 데이터 분석 (중급) - 8. Parametric Multiple Comparison with python
  9. 9파이썬을 활용한 데이터 분석 (중급) - 9. Kruskal-Wallis Rank Sum Test with python
  10. 10파이썬을 활용한 데이터 분석 (중급) - 10. Non-Parametric Multiple Comparison with python
  11. 11파이썬을 활용한 데이터 분석 (중급) - 11. Summary
Statistics (Harvard Stat110)9편
  1. 1ch1. Probability and Counting
  2. 2ch2. Story Proofs, Axioms of Probability
  3. 3ch3. Birthday Problem, Properties of Probability
  4. 4ch4. Conditional Probability
  5. 5ch5. Conditioning Continued, Law of Total Probability
  6. 6ch6. Monty Hall, Simpson's Paradox
  7. 7ch7. Gambler's Ruin and Random Variables
  8. 8ch8. Random Variables and Their Distributions
  9. 9ch9. Expectation, Indicator Random Variables, Linearity
분자생물학8편
  1. 11. DNA, RNA, Protein
  2. 22. DNA 구조와 핵산 기술
  3. 33. DNA 복제
  4. 44. 돌연변이와 DNA 수선
  5. 55. 유전자 전사와 RNA 가공
  6. 66. 원핵생물의 전사조절
  7. 77. 진핵생물의 전사조절
  8. 88. 단백질 합성
Sort Algorithm8편
  1. ·Special Sort Algorithm - Counting Sort
  2. ·Special Sort Algorithm - Radix Sort
  3. ·Advanced Sort Algorithm - Heap Sort
  4. ·Advanced Sort Algorithm - Merge Sort
  5. ·Advanced Sort Algorithm - Quick Sort
  6. ·Sort Algorithm - Bubble Sort
  7. ·Sort Algorithm - Insertion Sort
  8. ·Sort Algorithm - Selection Sort
Long Read Sequencing7편
  1. 1Long Read Sequencing I - Introduction
  2. 2Long Read Sequencing II - 유전체 지도 작성 개괄
  3. 3Long Read Sequencing III - 유전체 크기 추정하기
  4. 4Long Read Sequencing IV - Repeat/Gene Annotation
  5. 5Long Read Sequencing V - Assembly Quality 확인
  6. 6Long Read Sequencing VI - SV Calling
  7. 7Long Read Sequencing VII - Visualization
Epigenetics6편
  1. 1Epigenetics I - 후성유전학의 개요
  2. 2Epigenetics II - 크로마틴 구조
  3. 3Epigenetics III - 히스톤 변형과 DNA 메틸화
  4. 4Epigenetics IV- ncRNA에 의한 전사조절
  5. 5Epigenetics V- 세포운명 결정의 후성유전학
  6. 6Epigenetics VI - 후성유전체 데이터 생산과 분석1
유전자검사기관 교육6편
  1. ·Genetic Testing Agency Training 6 - 검사대상자의 권리
  2. ·Genetic Testing Agency Training 4 - 유전자검사기관의 의무 및 책임
  3. ·Genetic Testing Agency Training 5 - 유전자검사기관의 숙련도 평가
  4. ·Genetic Testing Agency Training 3 - 유전자검사항목의 신고
  5. ·Genetic Testing Agency Training 1 - 유전자검사의 이해
  6. ·Genetic Testing Agency Training 2 - 유전자검사 제도의 이해
생물정보학을 위한 R프로그래밍5편
  1. 1생물정보학을 위한 R프로그래밍 I - R 설치 및 환경설정
  2. 2생물정보학을 위한 R프로그래밍 II - 데이터형과 연산
  3. 3생물정보학을 위한 R프로그래밍 III - 데이터형과 연산
  4. 4생물정보학을 위한 R프로그래밍 IV - 데이터 취득과 정제
  5. 5생물정보학을 위한 R프로그래밍 V - 데이터 시각화
ML and DL for Cancer Genomics5편
  1. 1ML and DL for Cancer Genomics I - Bioinformatics Trend
  2. 2ML and DL for Cancer Genomics II - ML Basic Concpts and Evaluation Methods
  3. 3ML and DL for Cancer Genomics III - DL Algorithm I
  4. 4ML and DL for Cancer Genomics IV - DL Algorithm II
  5. 6ML and DL for Cancer Genomics VI - 딥러닝 구동 환경 구축 1
Transcriptome3편
  1. 1Transcriptome I - Introduction to Transcriptome
  2. 2Transcriptome II - Data Preprocessing
  3. 3Transcriptome III - Differential Expression & Visual Exploration
Guide to Linear Algebra3편
  1. 1ch1. Basic Mathmatics
  2. 2ch2. Introduce Linear Algebra
  3. 3ch3. Linear Algebra Calculations
Variants Analysis2편
  1. 5Variants Analysis V - Cancer Analysis
  2. 6Variants Analysis VI - Cancer Immunotherapy
Search Algorithm2편
  1. ·Search Algorithm - BFS (Breadth-First Search)
  2. ·Search Algorithm - DFS (Depth-First Search)