Free webinar-introduction to bioinformatics - biologist-1
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The Omics Logic Introduction to Bioinformatics program is a one-month online training program that provides an introduction to the field of bioinformatics for beginners. The program consists of six sessions taught by an international team of experts, covering topics like genomics, transcriptomics, statistical analysis, machine learning, and a final bioinformatics project. Participants will learn data analysis skills in Python and R and how to extract insights from multi-omics datasets with applications in biomedicine. The goal is to prepare students for data-driven research in life sciences through interactive lessons, coding exercises, and independent projects.
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Free webinar-introduction to bioinformatics - biologist-1
- 1. INTRODUCTION TO BIOINFORMATICS TAUBER Bioinformatics Research Center 𝜏 PROCESSING PIPELINES VISUALISATION DATA MINING INTERPRETATIONSTATISTICAL ANALYSIS Learn about the impact of the genomic revolution, next-generation sequencing - and computational technologies in every area of life sciences: Including - research, biomedical, biotechnology, and agrobiology.
- 2. BIOLOGY AS A DATA SCIENCE BIOLOGY DATA + Preparing biologists and clinicians for the influx of data, associated methodologies and data- driven research projects is as prominent as the emergence of computers for the tech industry. And while specialization and focus on the convergence of data, computer technologies and emerging molecular assays led to the expansion of bioinformatics as a field, more and more biologists and clinicians are expected to understand and handle their own data to publish and succeed in basic research. INTRODUCTION
- 3. OMICSLOGIC Harpreet Kaur, PhD Omicslogic Trainer Mohit Mazumder, PhD Omicslogic Project Mentor FACULTY: training and project support Expert: Molecular Biology & Biochemistry, Specialization: Cancer Genomics Research: Computer-aided Identification of Genetic Biomarkers for the Diagnosis and Prognosis of Liver Cancer. Expert: Bioinformatics & Structural Biology, Specialization: BioML & Data Science Research: Biomedical Big Data Research & Application of Machine learning, Collaborative Bioinformatics Projects INTRODUCTION TO BIOINFORMATICS
- 4. QUESTIONS!
- 5. INTRODUCTION STARTS: 13 OCTOBER 2020 Introduction to data-driven research and the age of high throughput data in life sciences The Genomics revolution that started with the human genome project and continues to this day Explore computer languages and operations that can help find patterns in data. Learn about integration of various biological data for vital research and industry applications. TAUBER Bioinformatics Research Center 𝜏
- 8. INTRODUCTION
- 10. The Omics Logic Introduction to Bioinformatics program is an introduction to the field of bioinformatics, or the intersection of informatics and biology. In this program, we will discuss the changing landscape of data-driven research in life sciences and the opportunities that come with the widely accessible high throughout technologies and computational methods for analysis and annotation of such detailed data in research and industry. We will discuss various data types, emerging technologies and their impact on health care, agriculture, environmental sciences, public health, and more. BIOINFORMATICS Dr. Joseph Smith
- 11. PROJECT-BASED METHODOLOGY Practical assignments embedded in a comprehensive theoretical curriculum Theoretical + hands-on + independent thinking + research experience
- 12. FOCUS & SPECIALIZATION It is widely acknowledged that to keep participants engaged, a topic of interest or domain expertise has to be the connecting glue for technical methods and practical skills being taught in a given module. The goal of specializations is to adopt a “domain expertise”-centered experience for theoretical and practical learning.
- 13. INDEPENDENT PROJECTS The transition from training to research is ability to generalize and apply learned skills to new challenges. Our training is designed to allow participants to apply methods to curated and new datasets and develop independent projects that showcase what has been learned in the context of a personal portfolio of projects.
- 14. YOUR PROJECT!
- 15. T-BioInfo is designed for processing, analysis and integration of multi-omics data. The platform is used in multiple research groups to extract meaningful insights from large multi-omics datasets. Our current effort expands to education, by enabling more people to extract meaningful, data-driven insights from omics datasets with biomedical applications. T-BIO.INFO | EDU.T-BIO.INFO | SERVER.T-BIO.INFO 15
- 16. 16 COLOR CODED MAPS EXPLANATION OF METHODS INPUTS & OUTPUTS REPRODUCIBLE WORKFLOWS
- 17. BIOINFORMATICS in R and Python https://code.omicslogic.com/ 3
- 18. Exercises designed to explain the code for visualisations in both R and Python OMICSLOGIC CODE PLAYGROUND
- 19. INTRODUCTION TO BIOINFORMATICS COURSE REVIEWS
- 20. QUESTIONS!
- 22. TAUBER Bioinformatics Research Center 𝜏 OMICSLOGIC ONLINE INTRODUCTION TO BIOINFORMATICS ✓ Bioinformatics and Big Data: Concepts and applications ✓ Introduction to Genomics: DNA Variants and Mutations ✓ Introduction to Transcriptomics: Gene Expression data analysis ✓ Introduction to BioML ( Statistical analysis and Machine Learning) ✓ NGS Data analysis in Python & R ✓ BioProject: Big Data in Biology
- 23. TAUBER Bioinformatics Research Center 𝜏 BIOINFORMATICS AND BIG DATA: CONCEPTS AND APPLICATIONS T-BioInfo: an intuitive and user-friendly interface for analysis of big data: NGS genomics and transcriptomics, mass-spectroscopy proteomics & metabolomics, structural biology, integration & machine learning, analysis of phenotypic & visual information.. Educational Materials and Projects: resource overview, topics and skillsets covered. INTRODUCTION TO BIOINFORMATICS OCTOBER 13 | 9 AM CST 2020
- 24. NCBI: What’s out there?
- 26. INTRODUCTION TO BIOINFORMATICS TAUBER Bioinformatics Research Center 𝜏 INTRODUCTION TO GENOMICS: DNA VARIANTS AND MUTATIONS Introduction to Next generation Sequencing: shotgun sequencing reads, the need for structured data and associated bioinformatics methods: processing (germline and somatic mutations), analysis (mapping, detecting variants) andinterpretation (significant and insignificant mutations, etc.) OCTOBER 15 | 9 AM CST 2020
- 28. 28 https://cancer.sanger.ac.uk/cosmic/mutation/overview?id=6549 combine_SRR925765_1__pair_combined_SRR925766_1__pair_combined.snvs.strelka.vcf CDS mutation, c.743G>T (Substitution, position 743, G➞T)
- 30. 30 Analysis of Genomic Data 1. pre-processing 2. mapping/alignment 3. variant calling 4. differential variant calling 5. annotation 6. post-processing
- 32. INTRODUCTION TO BIOINFORMATICS TAUBER Bioinformatics Research Center 𝜏 INTRODUCTION TO TRANSCRIPTOMICS: GENE EXPRESSION DATA ANALYSIS How we can measure functional proteins by the way of mRNA abundance and accurate identification of alternative splicing: an overview of RNA-seq, read quality and pre-processing, mapping on reference genome using various tactics (alignment and alignment-free quantification), Quantification of genes and transcripts. OCTOBER 20 | 9 AM CST 2020
- 33. XID: Characterized by the absence of the thymus, mutant B lymphocytes, and no T- cell function. NOD SCID: Severe combined immunodeficiency, with no mature T cells and B cells. Athymic Nude: Lacks the thymus and is unable to produce T-cells CB17 SCID: Severe combined immunodeficiency affecting both B and T lymphocytes. They have normal NK cells, macrophages, and granulocytes. Preparing Data For Analysis
- 34. 34 COLOR CODED MAPS EXPLANATION OF METHODS INPUTS & OUTPUTS REPRODUCIBLE WORKFLOWS
- 35. Patient Xenograft Cell line-based response prediction strategy
- 36. TAUBER Bioinformatics Research Center 𝜏 INTRODUCTION TO BIOML ( STATISTICAL ANALYSIS AND MACHINE LEARNING) Using statistical approaches to study processing pipeline outputs, perform exploratory data analysis, hypothesis testing, data mining and classification.Methods on comparative data analysis, association and visualization of complex and high dimensional data using the T- BioInfo platform INTRODUCTION TO BIOINFORMATICS OCTOBER 22 | 9 AM CST 2020
- 37. Finding Relationships in Data Eye color Gender Height (m) Weight (kg) Age blue female 1.65 62.7 29 blue female 1.50 57.0 31 blue female 1.69 64.2 18 blue male 1.58 63.2 31 green male 1.76 70.4 44 green male 1.82 72.8 26 green male 1.92 76.8 33 green female 1.54 61.6 39 green female 1.76 70.4 22 brown female 1.67 66.8 34 brown female 1.47 58.8 41 brown male 1.69 71.0 23 brown male 1.78 74.8 35 brown male 1.83 76.9 20 brown female 1.62 87 62 blue male 1.87 86.5 23 brown male 1.76 92 65 brown male 1.62 59 13 green female 1.70 59 32
- 38. Finding Relationships in Data Eye color Gender Height (m) Weight (kg) Age blue female 1.65 62.7 29 blue female 1.50 57.0 31 blue female 1.69 64.2 18 blue male 1.58 63.2 31 green male 1.76 70.4 44 green male 1.82 72.8 26 green male 1.92 76.8 33 green female 1.54 61.6 39 green female 1.76 70.4 22 brown female 1.67 66.8 34 brown female 1.47 58.8 41 brown male 1.69 71.0 23 brown male 1.78 74.8 35 brown male 1.83 76.9 20 brown female 1.62 87 62 blue male 1.87 86.5 23 brown male 1.76 92 65 brown male 1.62 59 13 green female 1.70 59 32
- 39. INTRODUCTION TO BIOINFORMATICS TAUBER Bioinformatics Research Center 𝜏 NGS DATA ANALYSIS IN PYTHON & R Methods on NGS comparative data analysis, association and visualization of complex and high dimensional data using the T-BioInfo platform and R studio and Python. Coding challenges and problems that get you motivated to think outside the box and learn about biological phenomena as you gain coding skills . OCTOBER 27 | 9 AM CST 2020
- 40. Welcome back, Elia BrodskyBio.Info ABOUT LOGOUT YOUR PROGRESS: NOTIFICATIONS: 25TOTAL POINTS: 2850 COMPLETED TASKS: 10/40 Practice Code in These Tutorials:
- 41. INTRODUCTION TO BIOINFORMATICS TAUBER Bioinformatics Research Center 𝜏 BIOPROJECTS NCBI & TCGA Repositories, Planning your project proposal, how to present your scientific data and hypothesis, Q&A sessions, Audio & Video Presentation, Case Studies & Publications, Datasets. OCTOBER 29 | 9 AM CST 2020
- 42. YOUR PROJECT!
- 43. TAUBER Bioinformatics Research Center 𝜏 INTRODUCTION TO BIOINFORMATICS ✅ 1-month Online Training Program ✅ For Beginners in Bioinformatics ✅ 6 Session | International Team of Experts ✅ Python and R | BIG DATA | Code Playground ✅ Statistics | Data Science and Biomedicine ✅ AI-guided Cloud Based Tools & Platforms ✅ ML | Multi Omics Data Analysis | 24/7 Support ✅ Certificate of Excellence | Bio Project Learn about the impact of the genomic revolution, next-generation sequencing - and computational technologies in every area of life sciences: Including - research, biomedical, biotechnology, and agrobiology.
- 44. QUESTIONS!
- 47. QUESTIONS!
Editor's Notes
- Hello everyone, welcome to this Online session to learn about Online Bioinformatics Training, we will start in two mins. The Omics Logic Introduction to Bioinformatics program is an introduction to the field of bioinformatics, or the intersection of informatics and biology. In this program, we will discuss the changing landscape of data-driven research in life sciences and the opportunities that come with the widely accessible high throughout technologies and computational methods for analysis and annotation of such detailed data in research and industry. We will discuss various data types, emerging technologies and their impact on health care, agriculture, environmental sciences, public health, and more.
- Biology is rapidly acquiring the character of a data science. Billions of data points on genes, proteins and other molecules are compiled in large files and systematically studied. Analyzing this data will lead to more knowledge and understanding about living organisms, including human health, biotechnology, crops and livestock. This course will give an overview of bioinformatics for students, biologists and clinicians. The influx of data, associated methodologies and data-driven research makes bioinformatics for life sciences as prominent as the emergence of computers for the tech industry.
- The program will be guided by highly experienced mentos with doctorate degrees in bioinformatics and computational biology
- So during the meeting we will pause in between to address your questions that you can put in the chat box. Also I would request everyone to keep their microphone muted for now and we will have a Q&A Session towards the end.
- Preparing biologists and clinicians for the influx of data, associated methodologies and data-driven research projects is as prominent as the emergence of computers for the tech industry. More and more biologists and clinicians are now expected to understand and handle their own data to publish and succeed in basic and translational research. In fact, biology itself is rapidly acquiring the character of a data science. Billions of data points on genes, proteins and other molecules are compiled in large files and systematically studied. This program will give a comprehensive overview of bioinformatics for students, biologists and clinicians.
- We will combine online interactive sessions, self-guided study materials and practical assignments for an immersive experience that has proven to be effective in our well-known and respected Omics Logic Bioinformatics Training programs.
- The coursework will provide introductory materials that have been taken by thousands of people from all over the world
- Online courses cover important terminology and provide a perspectives from experts on this exciting field. Each course has quizzes that allow you to see how much you have learned
- All of the activity is measured using our point system that lets us identify any technical issues and resolve roadblocks that are so common for bioinformatics. At the end of the program, each student will receive a personal certificate of participation
- You will also experience our project-based approach to learning bioinformatics. We take datasets from high impact publications and use them for practical exercises.
- These projects include such topics as oncology, neuroscience, agriculture and others.
- As a result, anyone starting on this journey in bioinformatics can start developing a project of their own.
- By seeing how experts analyze their data and achieve research results, you can start developing a research question of your own, identify the appropriate type of data and planning your analysis.
- For the duration of the program, we will be using the T-BioInfo platform to process big datasets. this platform is built for multi-omics integration and analysis of structured data with advanced methods like machine learning and mathematical modeling.
- This analytical platform will provide hands-on experience for anyone to apply the learned skills to interesting datasets with color-coded logical maps, explanation of methods, detailed input and output formats and reproducible workflows.
- Downstream analysis and visualization of processed data can be performed in popular coding languages R and Python, so we will offer an introduction to several basic methods and popular packages used in bioinformatics
- From visualization of genomic data to exploratory analysis and hypothesis testing
- This course provides a broad overview, but is structured to offer significant depth, even for the experienced. After completing this short introduction, you will be inspired to continue learning about this exciting field of bioinformatics.
- Let me pass it on to Our Omicslogic trainer to introduce herself and talk about her experience.
- In 6 interactive sessions, you will get to see the broad applications of next generation sequencing, biostatistics, and tool for big data analysis. In practical assignment, we will be learning about the logic of bioinformatics and see how data science methods can be used to study biology. In conclusion, you will also be able to plan how to take what you have learned and apply it to an independent research project using tools and methods we cover in the program.
- The resources and the data tell us a clear story. That as a scientist as a researcher as a student capable of becoming scientist now has the opportunity to do research by
- The program is designed to highlight the role of BIG OMICS DATA - that is shaping modern biomedical innovation where molecular data is used for precision diagnostics, big data integration and machine learning are transforming personalization of treatment selection and innovative algorithms allow for unprecedented capabilities with drug discovery, design of large molecules and drug repurposing.
- Why study genomics? Genomics is an essential subfield of bioinformatics, and a major force in expanding human knowledge of genetic associations with disease and other traits. It is an interdisciplinary field, including the development of methods for DNA sequencing, as well as for big data analysis of genomic sequences. Next-Generation Sequencing (NGS) techniques allow for whole-genome sequencing, and analysis of epigenetic factors such as DNA-protein interactions and DNA methylation with unprecedented efficiency. Massive databases for biological sequence data such as GenBank (National Center for Biotechnology Information), EMBL (European Bioinformatics Institute), and SRA allow for data-driven research and knowledge discovery. Large amounts of data such as from the 1000 Genomes Project are publicly available, providing anyone with the proper analytical skills and resources the opportunity for scientific discovery. While transcriptomics seeks to find variation in gene expression through methods such as RNA sequencing, genomics studies genome-wide genetic variation at the fundamental level of DNA sequences. The understanding of genetic associations provided by genomic research have great value in medicine, agriculture, ecology, biotechnology, and many other industries.
- This analytical platform will provide hands-on experience for anyone to apply the learned skills to interesting datasets with color-coded logical maps, explanation of methods, detailed input and output formats and reproducible workflows.
- Let’s say we collected data on eye color, gender, age, height and weight of people. We hypothesise that some variables here are related and some are not. We also think there are exceptions to the rule - the age and height or weight are related but not always… (~) Relationships observed in data can show which variables are related unrelated if related, then by how much? (more or less related)
- For example, weight and height seem to be logically related. Are they in this data set? If we plot a trend line, we will find that the trend line goes up - the higher the height, weight also increases. But the dots are not too close to the line, some dots seem to be far away from it. Is there a way to quantify this relationship we found?
- Once you have prepared the data, we will also explore the code behind each step so that you can understand how it works and modify it to fit your project needs.
- This introductory course leads into multiple courses and projects that can serve as a springboard into the world of bioinformatics.
- So this one month bioinformatics training program will include several components as you can see. If you have any questions
- Please go ahead and Now let me look at the chats.
- Let me now pass it to Ms. Beepsa Biswas who is our community manager and she will be able to guide you with program registration and access to the various resources that we discussed today.
- https://www.linkedin.com/groups/12246495/ https://www.facebook.com/groups/508888579450472/