강의계획서 202101.xls

	A	B	C	D	E	F	G	H	I	J	K	L	M	N	O	P	Q	R	S	U	V	W
1					수업 계획서
2					수업 계획서
3		교과목 정보	수업년도				2021			수업학기		1학기		학수번호			LIF4015		수업코드		11388
4			교과목명(국문)				시스템생물정보학							과목구분			전공심화
5			교과목명(영문)				SYSTEMS BIOLOGY							과목구분			전공심화
6			학점				2				강의	2		실습			0
7			설강조직				생명과학과							관장조직			생명과학과
8			강의시간				화 15:00-17:00 자연과학관 227강의실
9		교강사 정보	소속				생명과학과								성명			남진우
10			연락처												E-MAIL			jwnam@hanyang.ac.kr
11			홈페이지
12		수업운영	수업진행형태				토론식수업,소집단수업
13		수업운영	강의평가유형 (학생비공개)
14		교과목개요	Systems biology is an integrated (convergent) discipline of computational biology and differential equation-based systems and often applied to biomedical researches for understanding the larger picture—be it at the level of the organism, tissue, or cell—by putting its pieces together. It's in stark contrast to decades of reductionist biology, which involves taking the pieces apart. Systems biology is based on the computational and mathematical analysis and modeling of complex biological systems.
15		수업목표 및 안내	*This course runs with PBL-like programs including a team project and research activity. This class will cover the computational and statistical approaches to examine and understand cell-, tissue-, and organism-systems in the molecular (transcriptomic and/or genomic) levels. Student will learn how to analyze high-throughput sequencing dataset of personal transcriptomes and genomes and how to find the association with the phenotypes (often diseases). Particularly, student will have a chance to plan their research project and to present its research proposal about what they are going to investigate and how they analyze their genomic and/or transcriptomic sequences. For the planning project, selected students will have a chance to sequence their DNA or RNAs from their own blood. For the human study, student will understand why we need to consider ethical problems and learn how to submit an IRB application for the approval. Through this class, student may acquire abilities to design RNA-seq experiments, process the RNA-seq data, and interpret their largescale sequence data.
16		세부목표1	To learn how to interpret personal genomic and/or transcriptomic data
17		세부목표2	To learn computational methods to preprocess, analyze, and visualize sequences.
18		세부목표3	To interpret biological and clinical meanings of genomic and transcriptomic results.
19		교과목 주요주제	Student will learn how to analyze high-throughput sequencing dataset of personal transcriptomes and/or genomes and how to find the association with the phenotypes (often diseases).
20		선수과목 안내	1. Passion for learning computer programming (Python or similar ones) and computational genomics. 2. A little experiences for Unix (or Linux)-os system.
21		수강생 유의사항	1. 각 교과목 중 총 수업시간수의 3분의 2이상을 출석하여야만 그 교과목의 시험에 응시할 수 있다. 2. 시험관련 부정행위자로 판명되었을 때는 학칙 또는 내규에 의거 해당 교과목의 성적을 취소한다.
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23		장애학생 수업안내	장애학생은 본 수업과 관련하여 본인 희망시 다음과 같은 지원이 가능합니다. 담당교수 및 장애학생지원센터와 상담 바랍니다. * 공통: 도우미 지원(수업,이동), 대체평가, 별도 시험장소 제공, 선수강 지원, 노트북 사용 * 시각장애: 점자/확대/녹음 교재 및 시험지 제공, 시험시간 연장, 강의자료 텍스트제공 * 청각장애: 지정좌석제, 동영상 자막지원 * 지체장애: 강의실 변경, 지정좌석제, 시험시간 연장 ˂문의˃ : 장애학생지원센터 (서울) 02-2220-0776, (ERICA) 031-400-4502
24		교재	순번	교재명									저자			출판사				ISBN		가격
25		교재	조회된 데이터가 없습니다.
26		부교재	순번	교재명									저자			출판사				ISBN		가격
27		부교재	조회된 데이터가 없습니다.
28		평가항목	평가항목						비율					평가항목					비율
29			출석						10					퀴즈					0
30			과제						20					중간고사					40
31			토론						0					기말고사					0
32			팀프로젝트						30					학습참여도					0
33			기타 평가항목																비율
34																			%
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40			합계 100 %
41		주별 강의계획 및 과제	1			주제		Orientation
42	Orientation (Project team, NGS-RNA-seq presentaton, IRB, RFP). 1. Project teams: six teams will be organized today, each of which comprises 2~3 students along with a graduate student. The members in a team will collaborate each other for an RNA-seq project. Each team will discuss and determine a research plan with a specific goal and decide means how to process and analyze data. Finally, they will organize a ppt presentation that summarizes their project accompliment at the end. 2. NGS/RNA-seq presentation. All teams will present one of following topics: an introduction of sequencing technology (1), 2nd next-generation sequecing (NGS or high-throughput sequencing, 2), 3rd generation NGS (1), and RNA-seq (2) in the 2nd week. Based on the evaluation of the presetnation, we will choose three teams which will be eligible for RNA-seq sampling. The selected teams have to elect one student who actullay serve a donator of blood sample for sequencing. 3. Internal review board (IRB): All studies dealing with biospecimen from human must have IRB approval before research begining. Principle investigator and researchers apply IRB research plan and application documents along with a proof of bio-ethics education to IRB committee about a month earlier. 4. Request for proposal (RFP): 41:56		1			활동사항		Orientation (Project team, NGS-RNA-seq presentaton, IRB, RFP). 1. Project teams: Project teams will be organized in the first week (today), each of which comprises 2~3 students. The team members are collaborating with each other for their project. Each team will bring up a research plan with a specific hypothesis and aim, and decide a methodology how to process and analyze data. Finally, they will organize a ppt presentation that summarizes their project accompliment in the final project presetnation. 2. NGS/RNA-seq presentation. All teams will present one of following topics: an introduction of sequencing technology (1), 2nd next-generation sequecing (NGS or high-throughput sequencing, 2), 3rd generation NGS (1), and RNA-seq (2) in the 3rd week. 3. Internal review board (IRB): All studies dealing with biospecimen from human must have IRB approval before research begining. Principle investigator and researchers apply an IRB research plan and application documents along with a proof of bio-ethics education to IRB committee. 4. Request for proposal (RFP): Once we learn how to deal with RNA-seq data through 5 to 8th week, each team will write up a research plan with a research goal together. The research plan should include a title, team members, keywords, introduction, an aim, at least two subaims, experimental design & methods for each subaim, and expecting results or discussion in a word file. The proposal will be presetned at 10th and 11th weeks. 5. others: evaluation, mid-term exam, and term project.
43			2			주제		Personalized Genomics Era and Personal Transcriptomes (Lecture 100)
44			2			활동사항		Introduction of personalized genomics and transcriptomics through NGS and RNA-seq and their applications. We briefly review NGS/RNA-seq technology and their biological and clinical applications in this week. 0) Michael Snyder: "Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes", Cell 2012; "Personal omics profiles: "Integrative Personal Omics Profiles during Periods of Weight Gain and Loss", Cell Systems, 2018. 1) NGS for cancers: will discuss how to detect cancer-deriving somatic mutations and apply NGS to cancer therapy. 2) NGS as rare disease application: will discuss how to identify somatic and germline mutations whihc are molecular causal factors related to rare diseases using NGS. 3) Radiation-Genome interaction and wholegenome sequencing for detecting germline mutations. 4) 23&Me, Nebula genomics: direct to customer (DTC) DNA test services, 5) personal transcriptomics and application for drug development. 6) cancer-immuno therapy and single-cell RNA-seq: will discuss how to apply single-cell RNA-seq cancer-immuno therapy and personalized therapy.
45			3			주제		Sequencing technologies: Sanger sequencing (1st), Next-generation sequecing (2nd), long-read sequencing (3rd), and RNA-seq.
46			3			활동사항		1. Team presentation: Each team will present one of following topics for 10 minutes along with 5' discussion. Topics are an introduction of sequencing technology (1 team), 2nd next-generation sequecing (NGS or high-throughput sequencing, 1 team), 3rd generation NGS (1 team), and RNA-seq (1 team). 2. After Discussion: we will discuss base-calling procedure of NGS and the quality scores. In addition, students will discuss RNA-seq technologies with comparisons with 1st adn 3rd generation seqeuncing and will learn which biological problems can be examined by high-throughput RNA sequencing (RNA-seq). 3. Selection of three blood-donor volunteers.
47			4			주제		How to write and apply IRB.
48			4			활동사항		Internal review board (IRB): All studies dealing with biospecimen from human must have IRB approval. Principle investigator and researchers apply IRB research plan and application documents along with a proof of bio-ethics education to IRB committee about a month earlier. 1) IRB application: Student will learn why we need to consider bio-ethics during human-related studies, how to write IRB application and research plan under regulation of bio-ethics, and how to apply the IRB application. 2) Bio-ethics education: Prior to IRB application, all researchers have to have a certificates of bio-ethics education. Student will take an online bio-ethics course to get a certificates of bio-ethics education. IRB Committe at HYU: http://mrcc.hanyang.ac.kr/committee/irb_site.php?ptype=view&idx=8169&page=1&code=irb_faq. *** You should send your certificate for the online course back to TA.
49			5			주제		RNA-seq SOP 1, QC Mapping, preprocessing. /. * During this week, blood sampling will be carried out at hospitial (한양대학교 진단검사의학과).
50			5			활동사항		RNA-seq is a highly parallel sequencing technology that sequences all RNAs (transcriptome) in cells. Tissues, cell lines, or conditioned samples will be used to extract total RNAs for this RNA-seq. In principle, there are ~ 1 million RNA molecules in an average mammalian cell, comprising mRNAs, rRNA, tRNA, miRNA, lncRNA, snRNA, and so on. Although the fraction differ across cell types and status, rRNAs are the most abundant in a cell. When performing RNA-seq, researchers try to enrich target RNAs (mRNA and other ncRNAs except for rRNA) or deplet rRNAs using several experimental and computational methods. Once target RNAs are enriched, the RNA samples are input to make a RNA-seq library. There are multiple experimental steps including random fragmentation, RT-PCR, adaptor attachment, cloning, bar-coding, etc, for the construction of RNA-seq library but the combination and oreder of the stem could make differnt type of libraries. Once RNA-seq library is availble, it means that you are ready to submit the sample for RNA-seq. In a general purpose, we sequence ~ 4-6Gb of RNA-seq reads per sample (~20-30 million reads). In this section of RNA-seq SOP1, students will learn how to handle the raw RNA-seq results (fastq files), how to check the quality of reads (quality control steps) with qualtiy scores, how to preprocess reads (removing adaptors, errorneous bases, ..), and map the reads to the reference genomes. In addition, student will learn how to read fastq, sam, bam, bed and gff files and how to convert them.
51			6			주제		RNA-seq SOP 2, Assembly & Genomic profiling
52			6			활동사항		In cells, there might be unknown (never reported) transcripts of novel genes or new isoforms. Recently, ENCODE and similar transcriptome projects discovered unprecendently prevalent RNA molecules in genomes, approximateldy 60% of which are transcribed. The majority of unknown transcripts appear to be non-coding RNAs and new isoforms. In addition, there are many reports of abnormal transcripts embedding point and structural alterations and ones fused with other transcripts, mostly from disease-state cells, such as cancers. Importantly, there may be mutated RNAs (contained in exosomes or protein-protected in serum) originated from remote disease cells (tumor, inflammation, ...) in blood, some of which can be detected by liquid biopsy. Thus, RNA-seq allows us to identify those unknown and abnormal transcripts in cells. In this section of RNA-seq SOP 2, students will learn how to assemble reads to reconstruct a transcript (or transfrag), which allows us to annotate gene structures (transcription start & end, exon-intron structures) and identify new genes or isoforms, and how to visualize and compare the resulting transcriptomes with the known gene annotations. In addition, this section will cover how to detect genomic variations and fusion genes only using RNA-seq without DNA sequencing, which allows us to profiles somatic and germline mutations, allele-specific expression, and structural variations.
53			7			주제		RNA-seq SOP 3, Quantification & DEG & Isoform analysis
54			7			활동사항		All mapped reads to genomes were subjected to a quantification method that counts reads mapped to exonic loci of each gene or to transcript (or isoform). The counts are then normalized by the number of total mapped reads and by the length of exons (by 1kb), to be a quantification metric, RPKM or FPKM: reads (or fragments) per kilo-bases of exons per million mapped reads. The RPKM (or FPKM) can be converted other quantificaito metrics, such as TPM (transcript per million mapped reads), if necessary. If there are two different conditions, you may want to compare them to identify significantly changed genes or isoforms, which gives us identification of genes responding to different conditions and status (undifferentiated vs differentiated; normal vs tumor; control vs drug-treated..). However, the quantification of genes using RNA-seq sometimes suffers from stochastic process in read-count, experimental and technical errors, and biological variations so that we have to test whether the change of gene expression is statistically signficant with parametric methods (negative binomial test for read level; paired t-test for value level). In this section of RNA-seq SOP 3, students will learn how to quantify the level of protein-coding genes and noncoding RNA genes in the gene and transcript (isoforms) levels and how to detect significantly changed genes (or differnetially expressed genes, DEG) or isoforms in two differnt conditions (normal vs cancer, hypoxia vs normal, control vs starvation..) using several diffent computational methods.
55			8			주제		RNA-seq SOP 4, Immune profiling, GO, GSEA analysis
56			8			활동사항		Blood include peripheral blood mononuclear cells(PBMC - monocyte, T cell, B cell, NK cell), cells with no nunclear (erythrocyte and platelet), and multinuclear cells (granulocytes-neutrophil, basophil, eosinophil) in bloods. During RNA-seq, the majority of RNAs come from such blood cells. Individual blood contains different composition of those blood cells, some have higher lymphocyte contents than others, indicating immune-enriched condition. Because RNA-seq captures a pooled RNA samples from differnt cells, we cannot sort out which RNAs are from which type of cells unless performing doconvolution (sort of factorization). Thanks to computational deconvolution method (in silico cytometry), we can now predict the composition of blood cell-types, which allow us a certain level of clinical conditions of individual. On the other hand, gene sets responded to a certain condition or enriched to certain cell-types may indicate a biochemical or regulatory pathways related to the condition or the cell-types. Computational frameworks such as Gene ontology (GO) and Geneset enrichment analysis (GSEA) provide functional view of gene sets with interests. In this section of RNA-seq SOP 4, student will learn how to measure the fraction of certain immune cell-type from bulk RNA-seq data using computational deconvolution methods (such as Cybersort, Times, iCytometry) and to perform functional annotation of given gene sets using GO and GSEA. After the analyses, students may predict or intepret how the blood condition of the individual is based on the results.
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58		주별 강의계획 및 과제	9			주제		Mid-term exams
59			9			활동사항		Mid-term exams: questions will be asked from all materials provided during Week1 ~ Week 8. Subjects 1) sequencing technologies &. applications; 2) Personal omics, 3) RNA-seq 4) IRB and bio-ethics. The exam will consist of mulitpe-choice, short-answer, and essay question.
60			10			주제		Research proposal, presentation 1st round (all teams)
61			10			활동사항		All teams have to submit the Resaerch Proposal (word file) and PPT slides by this week (due: Tuesday 9AM). All teams will present their research proposal, which will be evaluated by peers and TA. Evaluation sheet will be distributed to each student and TA. Each peer (student) will score 1 (lowest) to 5 (highest) in terms of clarity, organization, and presentation quality for each presentaiton. The sum of the scores will be added to the project score. 1) Research proposal: the proposal should include a title, team members, keywords, introduction, an aim, at least two subaims, experimental design & methods for each subaim, and expecting results or discussion in a word file (font: times new roman, size: title-12, others: 10, space: single-space; upto 2 pages excluding a cover page). 2) Discussion & Feedback: All student and TA will give feedbacks and suggestions to each proposal to improve the research direction and methodologies. All teams should revise and resubmit their proposal and PPT slides by the next class.
62			11			주제		Research proposal, presentation 2nd round (All teams)
63			11			활동사항		All teams have to submit the revised Resaerch Proposal (word file) and revised PPT slides by this week (due: Tuesday 9AM). All teams will present their research proposal, which will be evaluated by peers and TA. Evaluation sheet will be distributed to each student and TA. Each peer (student) will score 1 (lowest) to 5 (highest) in terms of clarity, organization, and presentation quality for each presentaiton. The sum of the scores will be added to the project score. 1) Research proposal: the proposal should include a title, team members, keywords, introduction, an aim, at least two subaims, experimental design & methods for each subaim, and expecting results or discussion in a word file (font: times new roman, size: title-12, others: 10, space: single-space; upto 2 pages excluding a cover page). 2) Discussion & Feedback: Everyone will express comments and suggestions to each team. All teams have to address raised comments and suggestions in the final project.
64			12			주제		RNA-seq study examples 1: Tumor analysis using RNA-seq
65			12			활동사항		For cancer diagnosis and therapy, our and other conuntries are setting up the NGS-based platform to analyze DNA and RNAs from tumor specimen and peripheral blood in hostpitals. Our government started to provide the NGS-based (companion) diagnosis for rare genetic diseases, solid tumor, and blood tumors in medicare coverage in five major hospitals. In present, all companion diagnosis (predicting therapeutic markers for target therapy) are relied on the prediction of somatic (or germline) mutations and fusion genes in diseases. However, RNAs are becoming promising (or alternative) biomarkers that can provide more biological and clinical information in the future. In this section, we will discuss how to utilize RNA-seq for cancer diagnosis and prognosis, and how to find optimized diagnostic and prognostic RNA markers using real tumor samples. Student will go through all RNA-seq procedures (from QC, preprocessing, mapping, quantification, DEG, ..) to identify such RNA biomarkers.
66			13			주제		RNA-seq study examples 2: Gene signatures of sample clusters
67			13			활동사항		Some genes (i.e, house keepting genes) are ubiquitously expressed across different tissues or cell-types but others are specifically expressed in certain tissues or cell-types. This is also true in a specific condition and developmental stage. If you select two different cell-types (or conditions or stages), you can find differnetially expressed genes (DEGs). If you select multiple cell-types (or condition or stages), you can find sample groups with similar patterns of gene expressions and a gene signature representing a sample cluster. Although DEG analysis can provides a simple mean to find gene signatures, it requires multiple DEG analysis and multiple hypothesis correction and does ont guanrantee the optimal solution. There are multiple existing methods (a.k.a feature selection methods) to identify optimal gene signatures of sample clusters. Non-negative Matrix Factorization (NMF) and conditional mutual information are most popular methods. In this section, we will practice computational methods (k-means clustering, hierarchical clustering, principle component analysis (PCA), and NMF) that clusters sample groups with similar gene expressions, identify gene signatures of the clusters, and compare signatures from different clustering methods. For this practice, RNA-seqs of immune cell-types will be utilized.
68			14			주제		Project discussion & feedbacks
69			14			활동사항		Project presentation & evaluation: All teams should submit "Project presentation" ppt file that includes a title page (1 slide - title, authors, keywords- times new roman, 11~12pt), a project goal (1 slide), a summary of the project (1 slide), introduction (2 slides), results (upto 5 slides), discussion & conclusion (1 slide), acknowledge (1 slide) by this Tuesday midnight. The total length of the presentation slide should be less than 12 pages. In this week, students will present current processes with the ppt files (15 minutes including Q&A per each team). They can bring any inquiry, question, or problem that they came up with during the proejct. We will discuss all issues and questiosn with students together to find some solutions.
70			15			주제		Final project presentation
71			15			활동사항		Project presentation & evaluation: In this week, students will present their final results of the projects with their revised ppt files. All teams should submit "Project report" word file that includes a title page (tite, names with student number and affiliation, keywords - times new roman -12pt), an abstract (less than 500 characters with spaces, Arial-11pt), introduction (Arial-11pt), results (less than 5 pages; incl. at least three main figures or tables, Arial-11pt), discussion & conclusion (less than 2 pages, Arial-11pt), and acknowledgement (Arial-11pt), and references (times new roman, 11pt). The total length of the report have to be less than 10 pages including a title page. The figure and table should accompany with corresponding legends. The biliography (citations for references) should be appropriately added throughout the reports and they must be listed in the references.
72			16			주제		Class Review
73			16			활동사항		Class Review: All students and teachers will gather together to review the class and to exchange their feedbacks.
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