视频选集 1_STAT115 Chapter 2.1 Protein Wave.zh_en 2_STAT115 Chapter 2.2 Expression Wave.zh_en 3_STAT115 Chapter 2.3 Sequencing Wave.zh_en 4_STAT115 Chapter 2.4 Big Data Challenge.zh_en 5_STAT115 Chapter 2.5 Bioinfo vs Comp Bio.zh_en 6_STAT115 Chapter 2.6 Is Class Right For Me.zh_en 7_STAT115 Chapter 2.7 Course Information.zh_en 8_X Shirley Liu Liu Lab Introduction.zh_en 9_STAT115 Chapter 3.1 Three Generations of Sequencing.zh_en 10_STAT115 Chapter 3.2 FASTQ and FASTQC.zh_en 11_Local Sequence Alignment & Smith-Waterman __ 12_Global Sequence Alignment & Needleman-Wunsch __ 13_STAT115 Chapter 3.4 BLAST and Suffix Arrays.zh_en 14_STAT115 Chapter 3.5.1 BWT and LF Mapping.zh_en 15_STAT115 Chapter 3.5.2 Borrows-Wheeler Alignment.zh_en 16_STAT115 Chapter 3.6 SAM and BAM files.zh_en 17_2021 STAT115 Lab 1.1 Introduction.zh_en 18_2021 STAT115 Lab1.2 Intro to R.zh_en 19_2021 STAT115 Lab1.3 Intro to Bash.zh_en 20_2021 STAT115 Lab1.4 Intro to Harvard Cannon Cluster.zh_en 21_STAT115 Chapter 4.1 RNA-seq Applications.zh_en 22_STAT115 Chapter 4.2 RNA-seq Experimental Design.zh_en 23_STAT115 Chapter 4.3 RNA-seq Alignment.zh_en 24_STAT115 Chapter 4.4 RNA-seq QC.zh_en 25_RPKM, FPKM and TPM, Clearly Explained!!!.zh_en 26_STAT115 Chapter 4.6 RSEM vs Salmon.zh_en 27_STAT115 Chapter 4.6 RNA-seq Read Distribution.zh_en 28_StatQuest_ DESeq2, part 1, Library Normalization.zh_en 29_STAT115 Chapter 5.2 Differential RNA-seq.zh_en 30_ 5.3 Multiple Hypotheses Testing and False Discovery Rate.zh_en 31_StatQuest_ edgeR and DESeq2, part 2 - Independent Filtering.zh_en 32_STAT115 Chapter 5.5 Gene Ontology.zh_en 33_STAT115 Chapter 5.6 Gene Set Enrichment Analyses.zh_en 34_2021 STAT115 Lab2.1 STAR Tutorial.zh_en 35_2021 STAT115 Lab2.2 RSeQC Tutorial.zh_en 36_2021 STAT115 Lab2.3 RSEM_Salmon Tutorial.zh_en 37_STAT115 Chapter 6.1_2 Hierarchical Clustering.zh_en 38_STAT115 Chapter 6.3 K-means Clustering.zh_en 39_STAT115 Chapter 6.4 Considerations of Kmeans Clustering.zh_en 40_STAT115 Chapter 6.5 Batch Effect Removal.zh_en 41_2021 STAT115 Lab 3.1 PCA Tutorial.zh_en 42_2021 STAT115 Lab 3.2 Clustering Tutorial.zh_en 43_2021 STAT115 Lab 3.3 Combat Tutorial.zh_en 44_2021 STAT115 Lab 3.4 DESeq2 Tutorial.zh_en 45_2021 STAT115 Lab 3.5 GO, DAVID & GSEA Tutorial.zh_en 46-Chapter 7.1 Introduction to Principal Component Analysis (PCA).zh_en 47_Chapter 7.2 Principal Component Analysis (PCA) Applications.zh_en 48_STAT115 Chapter 7.3 Multidimensional Scaling (MDS).zh_en 49_STAT115 Chapter 7.4 Linear Discriminant Analysis (LDA).zh_en 50_A Gentle Introduction to Machine Learning.zh_en 51_Machine Learning Fundamentals_ Cross Validation.zh_en 52_StatQuest_ Logistic Regression.zh_en 53_Regularization Part 1_ Ridge (L2) Regression.zh_en 54_StatQuest_ K-nearest neighbors, Clearly Explained.zh_en 55_StatQuest_ Decision Trees.zh_en 56_StatQuest_ Random Forests Part 1 - Building, Using and Evaluating.zh_en 57_Support Vector Machines Part 1 (of 3)_ Main Ideas!!!.zh_en 58_2021 STAT115 Lab 4.1 K-Nearest Neighbors Tutorial.zh_en 59_2021 STAT115 Lab4.2 Regression Tutorial.zh_en 60_2021 STAT115 Lab4.3 Logistic Regression Tutorial.zh_en 61_2021 STAT115 Lab4.4 Support Vector Machine Tutorial.zh_en 62_2021 STAT115 Lab4.5 Random Forest Tutorial.zh_en 63_STAT115 Chapter 9.1 Module I Review.zh_en 64_STAT115 Chapter 9.2 Module I Review, Analysis Scenario 1.zh_en 65_STAT115 Chapter 9.3 Module I Review, Analysis Scenario 2.zh_en 66_STAT115 Chapter 10.1 Transcription Regulation.zh_en 67_STAT115 Chapter 10.2 Expectation Maximization for Motif Finding.zh_en 68_STAT115 Chapter 10.3 Gibbs Sampling for Motif Finding.zh_en 69_STAT115 Chapter 10.4 Motif Finding General Practices.zh_en 70_STAT115 Chapter 10.5 Motif Conservation and Modules.zh_en 71_STAT115 Chapter 11.1 ChIP-seq.zh_en 72_STAT115 Chapter 11.2 ChIP-seq Peak Calling with MACS and QC.zh_en 73_STAT115 Chapter 11.3 TF Interactions from ChIP-seq.zh_en 74_STAT115 Chapter 11.4 TF Target Genes from ChIP-seq.zh_en 75_2021 STAT115 Lab5.1 MACS Tutorial.zh_en 76_2021 STAT115 Lab5.2 ChIP-seq QC Tutorial.zh_en 77_2021 STAT115 Lab5.3 TF Motif Finding Tutorial.zh_en 78_2021 STAT115 Lab5.4 TF Collaborator Tutorial.zh_en 79_STAT115 Chapter 12.1 Intro to DNA Methylation.zh_en 80_STAT115 Chapter 12.2 DNA Methylation Pattern and Function.zh_en 81_STAT115 Chapter 12.3 DNA Methylation in Diseases.zh_en 82_STAT115 Chapter 12.4 Techniques to Measure DNA Methylation.zh_en 83_STAT115 Chapter 13.1 Nucleosome Positioning.zh_en 84_STAT115 Chapter 13.2 Introduction to Histone Modifications.zh_en 86_STAT115 Chapter 13.4 Using Histone Marks to Infer Gene Functions.zh_en 87_STAT115 Chapter 13.5 Introduction to DNase-seq and ATAC-seq.zh_en 88_STAT115 Chapter 13.6 Infer TF from Differential Genes Using LISA.zh_en 89_STAT115 Chapter 13.7 DNase-seq.zh_en 90_STAT115 Chapter 13.8 Summary of Epigenetics and Chromatin.zh_en 91_2021 STAT115 Lab6.1 ChIP-seq Expression Integration.zh_en 92_2021 STAT115 Lab6.2 Cistrome-GO Tutorial.zh_en 93_2021 STAT115 Lab6.3 ATAC-seq Analysis and LISA Tutorial.zh_en 94_STAT115 Chapter 14.1 Markov Chain.zh_en 95_STAT115 Chapter 14.2 Hidden Markov Model.zh_en 96_STAT115 Chapter 14.3 Hidden Markov Model Forward Procedure.zh_en 97_STAT115 Chapter 14.4 Hidden Markov Model Backward Procedure.zh_en 98_STAT115 Chapter 14.5 HMM Forward-Backward Algorithm.zh_en 99_STAT115 Chapter 14.6 Viterbi Algorithm.zh_en 100_STAT115 Chapter 14.7 Baum Welch Algorithm Intuition.zh_en 101_STAT115 Chapter 14.8 HMM Bioinformatics Applications.zh_en 102_STAT115 15.1 Introduction to Chromatin Interaction and Organization 103_STAT115 15.2 Methods to Investigate 3D Genome Organization 104_STAT115 15.3. Topologically Associating Domains.zh_en 105_STAT115 15.4 TAD Function and Loop Anchors.zh_en 106_STAT115 15.5 Chromatin Compartments.zh_en 107_STAT115 15.6 Computational Methods to Call Chromatin Loops 108_STAT115 15.7 Variations of Chromatin Interaction Technologies 109_STAT115 15.8 Resources for Exploring 3D Genomes.zh_en 110_2021 Lab7.1 BS-seq and Bismark Tutorial.zh_en 111_2021 Lab7.2 Tutorial on Associating DNA Methylation with Expression 112_2021 STAT115 Lab7.3 HiC Analysis Tutorial.zh_en 113_STAT115 Chapter 16.1 Module II Review.zh_en 114_STAT115 Chapter 16.2 Module II Analysis Scenarios.zh_en 115_STAT115 Chapter 17.1 SNP, LP, and Association Studies..zh_en 116_STAT115 Chapter 17.2 GWAS Studies and eQTL Analysis.zh_en 117_STAT115 Chapter 18.1 Intro Functional Annotate GWAS.zh_en 118_STAT115 Chapter 18.2 GWAS Functional Enrichment.zh_en 119_STAT115 Chapter 18.3 Find Causal SNPs.zh_en 120_STAT115 Chapter 18.4 Predict disease risk.zh_en 121_2021 STAT115 Lab 8.1 HW4 FAQ & cooler.zh_en 122_2021 STAT115 Lab 8.2 Pikachu&HiGlass.zh_en 123_2021 STAT115 Lab 8.3 HMM.zh_en 124_STAT115 Chapter 19.1 Intro to scRNA seq.zh_en 125_STAT115 Chapter 19.2 scRNA seq techniques.zh_en 126_STAT115 Chapter 19.3 scRNA seq preprocessing and QC.zh_en 127_STAT115 Chapter 19.4 Cleaning up expression matrix.zh_en 128_STAT115 Chapter 20.1 scRNA seq dimension reduction.zh_en 129_STAT115 Chapter 20.2 Clustering and projections.zh_en 130_STAT115 Chapter 20.3 Pseudo time and RNA velocity.zh_en 131_STAT115 Chapter 20.4 Clustering by genotype and CITE seq.zh_en 132_STAT115 Chapter 21.1 Single-Cell ATAC-seq Technique.zh_en 133_STAT115 Chapter 21.2 Single-Cell ATAC-seq Pre-Processing and QC 134_STAT115 Chapter 21.3 Single-Cell ATAC-seq Analysis.zh_en 135_STAT115 Chapter 21.4 scATAC-seq Integration with scRNA-seq 136_2021 STAT115 Lab9.1 MAESTRO Tutorial.zh_en 137_STAT115 Chapter 23.1 Introduction to Cancer Genome Analysis 138_STAT115 Chapter 23.2 Cancer. Mutation Characterization.zh_en 139_STAT115 Chapter 23.3 Cancer Mutation Patterns.zh_en 140_STAT115 Chapter 23.4 Tumor Purity and Clonality.zh_en 141_STAT115 Chapter 23.5 Interpret Tumor Mutations.zh_en 142_STAT115 Chapter 23.6 Find Cancer Genes.zh_en 143_STAT115 Chapter 23.7 Summary and Future.zh_en 144_STAT115 Chapter 24.1 Tumor Subtypes.zh_en 145_STAT115 Chapter 24.2 Survival Analysis.zh_en 146_STAT115 Chapter 24.3 Oncogenes and Tumor Suppressor Mutations 147_STAT115 Chapter 24.4 Cancer Epigenetics.zh_en 148_STAT115 Chapter 25.1 Introduction to Targeted Therapy.zh_en 149_STAT115 Chapter 25.2 Resistance to Targeted Therapy.zh_en 150_STAT115 Chapter 25.3 Model System Chemical and Genetic Screens 151_STAT115 Chapter 25.4 Overcoming Resistance Targeted Therapy.zh_en 152_STAT115 Chapter 26.1 Intro to Cancer Immunotherapy.zh_en 153_STAT115 Chapter 26.2 HLA and Neoantigen Presentation.zh_en 154_STAT115 Chapter 26.3 Immune Cell Infiltration in Tumors.zh_en 155_STAT115 26.4 T Cell Receptor Repertoires in Cancer Immunology 156_2021 STAT115 Lab10.1 TCGA exploration.zh_en 157_2021 STAT115 Lab10.2 LIMMA on microarray data.zh_en 158_2021 STAT115 Lab10.3 Survival analysis.zh_en 159_STAT115 Chapter 27.1 B Cell Receptor Repertoires in Tumors.zh_en 160_STAT115 Chapter 27.2 T Cell Activation and Dysfunction.zh_en 161_STAT115 27.3 NK Cells and Macrophages in Tumor Immunity.zh_en 162_STAT115 27.4 Cancer Immunotherapy Response Biomarkers.zh_en 163_STAT115 27.5 Improving Immunotherapy Response.zh_en 164_2021 Lab11.1 Cancer mutations and driver genes.zh_en 165_2021 Lab11.2 CRIPSR screen.zh_en 166_2021 Lab11.3 Cancer immunology.zh_en 167_STAT115 28.1 Introduction to CRISPR and CRISPR Screens.zh_en 168_STAT115 28.2 Computational Resources for CRISPR and Screens 169_STAT115 28.3 Cancer Cell Vulnerability from CRISPR Screens 170_STAT115 28.4 Immune Related CRISPR Screens.zh_en 171_Depmap tutorial.zh_en 172_STAT115 29.1 Module IV Review.zh_en 173_STAT115 29.2 Final Course Review.zh_en 174_STAT115 29.3 Final Exam Preparations.zh_en 175_STAT115 29.4 Levels of Bioinformatics and Preparing for the Future.
GPT中英字幕课程资源的视频 哈佛大学《生物信息学与计算生物学导论| Introduction to Bioinformatics and Computational Biology》中英 CMU《计算机系统导论|CMU 15-213，15-513，14-513 Introduction to Computer Systems 2017 CMU《机器学习导论|CMU Fall 2023 10-301/601 Introduction to Machine Learning》中英字幕 耶鲁大学《天才的本质|The Nature of Genius》中英字幕（gpt-4o 斯坦福大学《音乐应用的音频信号处理|Audio Signal Processing for Music Applications》中英字幕
