BIO390 - Introduction to Bioinformatics
Summary
The handling and analysis of biological data using computational methods has become an essential part in most areas of biology. In this lecture, students will be introduced to the use of bioinformatics tools and methods in different topics, such as molecular resources and databases, standards and ontologies, sequence and high performance genome analysis, biological networks, molecular dynamics, proteomics, evolutionary biology and gene regulation. Additionally, the use of low level tools (e.g. Programming and scripting languages) and specialized applications will be demonstrated. Another topic will be the visualization of quantitative and qualitative biological data and analysis results.
Practical Information
- Autumn semesters
- 1 x 2h / week
- Tue 08:00-09:45
- UZH Irchel campus, Y03-G-85
- OLAT - but not much there...
- KALTURA for lecture recordings
- videos are posted with some delay due to editing etc.
- Course language is English
Some very approximate learning goals may provide you with additional guidance - but plese be aware that those may not be particularly adjusted to a given course edition.
For entries of previous lectures please scroll down to the previous
entries.
Upcoming ¶
Statistical Bioinformatics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Mark Robinson
Continue readingMetagenomics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Shinichi Sunagawa (ETHZ)
(... to be confirmed ...)
Abstract:
Microorganisms are numerically dominant on Earth and drive the cycling of energy, elements and matter. Thanks to advances in high-throughput DNA sequencing technologies and computational power, microbial communities can now be studied without the need to cultivate them in a laboratory setting. Essential tasks in studying microbial communities include the identification and quantification of their member taxa and the pair-wise compositional comparison of different microbial communities.
Continue readingRegulatory Genomics and Epigenomics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Izaskun Mallona
Continue readingMachine Learning for Biological Use Cases
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Valentina Boeva (ETHZ)
(Date to be confirmed)
Brief note: In this lecture V. Boeva will cover the standard machine learning methods used in the analysis of biological data: dimensionality reduction, clustering, classification and regression.
Continue readingProteomics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Katja Baerenfaller, Swiss Institute of Allergy and Asthma Research (SIAF) and University of Zurich
In proteomics one of the important bioinformatics tasks is to generate lists of reliably identified peptides and proteins in mass spectrometry-based experiments. For this, amino acid sequences are assigned to measured tandem mass spectra. The quality of the peptide spectrum assignments are scored and criteria are applied that allow to distinguish the good from the bad hits and to estimate the quality of the dataset.
Continue readingBiological Networks
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Pouria Dasmeh
This part of the course BIO390 (Introduction to Bioinformatics) will review examples of biological networks their basic properties.
Continue readingText Mining and Search Strategies
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Patrick Ruch (HES-SO/HEG Geneva)
Search engines, stemming, NGRAMs ... and much more.
Continue readingComponents of the Semantic web
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Ahmad Aghaebrahimian (ZHAW)
(... to be confirmed ...)
Biomedical science is rich in structured and unstructured textual data including but not limited to hundreds of ontologies as well as millions of scientific publications. Semantic web and its stack of standards provide an efficient way for organizing knowledge extracted from such huge volume of data. Modeling data in knowledge graphs makes complex question answering and reasoning over abundance of information manageable and feasible. In this session we will find out how.
Continue readingBuilding a Genomics Resource
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Michael Baudis
In this lecture we will use our Progenetix resource, a website providing information about genomic copy number mutations in cancer - to present the different components needed for generating, storing, representing, visualizing and accessing a specific type of genomic data and associated classifications.
Continue readingClinical Bioinformatics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Valerie Barbie (Director SIB Clinical Bioinformatics)
Medical practice is undergoing a revolution around personalized health: this major change is driven by the continuous development of cost-effective high-throughput technologies that produce gigantic quantities of data in numerous areas, from imaging to genomics, and of the corresponding tools required to process these data.
Continue readingGenomic Data Risks & Opportunities
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Michael Baudis
The understanding of the impact of inherited and somatic genome variants on phenotypes and diseases requires a thorough understanding of such variants amongst populations in general and carriers of the phenotypes and diseases in particular. Such information can only be provided through the inclusion of data from a multitude of genome resources in variant evaluation efforts, including such from outside (international) jurisdictions. However, opening such resources carries the inherent risk of breaching privacy, particularly through re-identification of individuals or their relatives and potentially through the exposure of individual genome-related personal information including phenotypic and "performance" prediction and relative disease risk.
Continue readingBIO390 Exam
BIO390 UZH HS22 - Introduction to Bioinformatics08:15-09:45 @ UZH Irchel Y03-G-85
The exam will be on the last day of the course on site:
- time: 08:15-09:45
- multiple (single + multiple) choice w/ one or two open questions
- no material, phones etc.
- student ID for entrance
- please refer to the learning goals for guidance
- ¡topics may be edited throughout the course!
- these just provide some non-exclusive guidance
Previous ¶
What is Bioinformatics? Introduction and Resources
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Michael Baudis
This year happening at the second lecture day, the "What is Bioinformatics? Introduction and Resources" provides a general introduction into the field and a description of the lecture topics, timeline and procedures.
Topics covered in the lecture are e.g.:
- a term definition for bioinformatics
- the relation of hypothesis driven and data driven science, with respect to bioinformatics
- categories of bioinformatics tools and data
- research areas and topics
- the varying emphasis on "bio" and "informatics"
- databases (primary vs. derived) and data curation
- data collection & curation
- file Formats, ontologies & APIs ass areas/topics (w/o details)
- "not-bioinformatics"
Biological Sequence Informatics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Christian von Mering
The analysis of biological sequences - primarily DNA, RNA and protein sequences - constitutes one of earliest and core areas of bioinformatics. This lecture introduces principles and examples of bioinformatic sequence analyses and inter-sequence comparisons. Continue reading
BIO390 Repeat Exam
BIO390 UZH HS22 - Introduction to Bioinformatics
The repeat exam will be on January 24, 2023:
- time: 10:15-11:45
- Y03-G-85 (normal lecture hall, unless noted of change)
- multiple (single + multiple) choice w/ one or two open questions
- no material, phones etc.
- student ID for entrance
- please refer to the learning goals for guidance
- ¡topics may be edited throughout the course!
- these just provide some non-exclusive guidance
BIO390 Exam
BIO390 UZH HS22 - Introduction to Bioinformatics08:15-09:45 @ UZH Irchel Y03-G-85
The exam will be on the last day of the course on site:
- time: 08:15-09:45
- ¡¡¡ NEW: Room change to Y15-G-20 !!!
- multiple (single + multiple) choice w/ one or two open questions
- no material, phones etc.
- student ID for entrance
- please refer to the learning goals for guidance
- ¡topics may be edited throughout the course!
- these just provide some non-exclusive guidance
Genomic Data Risks & Opportunities
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Michael Baudis
The understanding of the impact of inherited and somatic genome variants on phenotypes and diseases requires a thorough understanding of such variants amongst populations in general and carriers of the phenotypes and diseases in particular. Such information can only be provided through the inclusion of data from a multitude of genome resources in variant evaluation efforts, including such from outside (international) jurisdictions. However, opening such resources carries the inherent risk of breaching privacy, particularly through re-identification of individuals or their relatives and potentially through the exposure of individual genome-related personal information including phenotypic and "performance" prediction and relative disease risk.
Continue readingClinical Bioinformatics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Valerie Barbie (Director SIB Clinical Bioinformatics)
Medical practice is undergoing a revolution around personalized health: this major change is driven by the continuous development of cost-effective high-throughput technologies that produce gigantic quantities of data in numerous areas, from imaging to genomics, and of the corresponding tools required to process these data.
Continue readingBuilding a Genomics Resource
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Michael Baudis
In this lecture we will use our Progenetix resource, a website providing information about genomic copy number mutations in cancer - to present the different components needed for generating, storing, representing, visualizing and accessing a specific type of genomic data and associated classifications.
Continue readingComponents of the Semantic web
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Ahmad Aghaebrahimian (ZHAW)
Biomedical science is rich in structured and unstructured textual data including but not limited to hundreds of ontologies as well as millions of scientific publications. Semantic web and its stack of standards provide an efficient way for organizing knowledge extracted from such huge volume of data. Modeling data in knowledge graphs makes complex question answering and reasoning over abundance of information manageable and feasible. In this session we will find out how.
Continue readingText Mining and Search Strategies
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Patrick Ruch (HES-SO/HEG Geneva)
Search engines, stemming, NGRAMs ... and much more.
Continue readingBiological Networks
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Pouria Dasmeh
This part of the course BIO390 (Introduction to Bioinformatics) will review examples of biological networks their basic properties.
Continue readingProteomics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Katja Baerenfaller, Swiss Institute of Allergy and Asthma Research (SIAF) and University of Zurich
In proteomics one of the important bioinformatics tasks is to generate lists of reliably identified peptides and proteins in mass spectrometry-based experiments. For this, amino acid sequences are assigned to measured tandem mass spectra. The quality of the peptide spectrum assignments are scored and criteria are applied that allow to distinguish the good from the bad hits and to estimate the quality of the dataset.
Continue readingMetagenomics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Shinichi Sunagawa (ETHZ)
Abstract:
Microorganisms are numerically dominant on Earth and drive the cycling of energy, elements and matter. Thanks to advances in high-throughput DNA sequencing technologies and computational power, microbial communities can now be studied without the need to cultivate them in a laboratory setting. Essential tasks in studying microbial communities include the identification and quantification of their member taxa and the pair-wise compositional comparison of different microbial communities.
Continue readingRegulatory Genomics and Epigenomics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Izaskun Mallona
Continue readingMachine Learning for Biological Use Cases
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Valentina Boeva (ETHZ)
Brief note: In this lecture V. Boeva will cover the standard machine learning methods used in the analysis of biological data: dimensionality reduction, clustering, classification and regression.
Continue readingStatistical Bioinformatics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Mark Robinson
Continue readingBiological Sequence Informatics
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Christian von Mering
The analysis of biological sequences - primarily DNA, RNA and protein sequences - constitutes one of earliest and core areas of bioinformatics. This lecture introduces principles and examples of bioinformatic sequence analyses and inter-sequence comparisons. Continue reading
What is Bioinformatics? Introduction and Resources
BIO390 UZH HS22 - Introduction to Bioinformatics08:00-09:45 @ UZH Irchel Y03-G-85
Michael Baudis
The first day of the "Introduction to Bioinformatics" lecture series starts with a general introduction into the field and a description of the lecture topics, timeline and procedures.
Topics covered in the lecture are e.g.: Continue reading
Clinical Bioinformatics
Valerie Barbie
Medical practice is undergoing a revolution around personalized health: this major change is driven by the continuous development of cost-effective high-throughput technologies that produce gigantic quantities of data in numerous areas, from imaging to genomics, and of the corresponding tools required to process these data.
Continue readingBuilding a Genomics Resource
Michael Baudis
In this lecture we will use our Progenetix resource, a website providing information about genomic copy number mutations in cancer - to present the different components needed for generating, storing, representing, visualizing and accessing a specific type of genomic data and associated classifications.
Continue readingBiomedical Text Mining
Fabio Rinaldi
What is text mining?
The ability to process text written in some human language (unstructured data), typically a large set of documents, interpret the meaning, and automatically extract concepts, as well as the relationships among those concepts, to directly answer questions of interest.
Continue readingBiological Networks
Pouria Dasmeh
In this part of the course BIO390 (Introduction to Bioinformatics), we review examples of biological networks, and get to know their basic properties.
Continue readingProteomics
Katja Baerenfaller (SIAF)
In proteomics one of the important bioinformatics tasks is to generate lists of reliably identified peptides and proteins in mass spectrometry-based experiments. For this, amino acid sequences are assigned to measured tandem mass spectra. The quality of the peptide spectrum assignments are scored and criteria are applied that allow to distinguish the good from the bad hits and to estimate the quality of the dataset.
Continue readingMetagenomics
Shinichi Sunagawa (ETHZ)
Abstract:
Microorganisms are numerically dominant on Earth and drive the cycling of energy, elements and matter. Thanks to advances in high-throughput DNA sequencing technologies and computational power, microbial communities can now be studied without the need to cultivate them in a laboratory setting. Essential tasks in studying microbial communities include the identification and quantification of their member taxa and the pair-wise compositional comparison of different microbial communities.
Continue readingMachine Learning for Biological Use Cases
Valentina Boeva (ETHZ)
Brief note: In this lecture V. Boeva will cover the standard machine learning methods used in the analysis of biological data: dimensionality reduction, clustering, classification and regression.
Continue readingBiological Sequence Informatics
Christian von Mering
The analysis of biological sequences - primarily DNA, RNA and protein sequences - constitutes one of earliest and core areas of bioinformatics. This lecture introduces principles and examples of bioinformatic sequence analyses and inter-sequence comparisons.
Continue readingWhat is Bioinformatics? Introduction and Resources
Michael Baudis
The first day of the "Introduction to Bioinformatics" lecture series starts with a general introduction into the field and a description of the lecture topics, timeline and procedures.
Continue readingClinical Bioinformatics
Valerie Barbie
Medical practice is undergoing a revolution around personalized health: this major change is driven by the continuous development of cost-effective high-throughput technologies that produce gigantic quantities of data in numerous areas, from imaging to genomics, and of the corresponding tools required to process these data.
Continue readingProteomics
Katja Baerenfaller
In proteomics one of the important bioinformatics tasks is to generate lists of reliably identified peptides and proteins in mass spectrometry-based experiments. For this, amino acid sequences are assigned to measured tandem mass spectra. The quality of the peptide spectrum assignments are scored and criteria are applied that allow to distinguish the good from the bad hits and to estimate the quality of the dataset.
Continue reading