- VBCF courses - lists.vbcf.ac.at

[VBC-SCIENCE] CBE HPC cluster intro course announcement
by Aszodi,Andras May 21, 2026

May 21, 2026

Dear Colleagues, I am pleased to announce the CBE HPC cluster introduction course which is highly recommended to all new users of the CBE cluster system. For details, see https://training.vbcf.ac.at/training/cbe.php . When? Tuesday the 2nd June from 09:00 to 13:00. Where? Physically in the IMP seminar room E-016 (preferred option), and remotely via teleconferencing. The latter option is ONLY for non-VBC employees and moderately sick colleagues. Who may attend? Anyone who may use the CBE system (IMP,IMBA,GMI,VBCF employees and external colleagues with cluster access). If you plan to use the cluster in the near future then you'll need a cluster account (see below). Cost? Free of charge. Pre-requisites: - You must have a CBE cluster account (our IT will set it up if needed). - VBC VPN access if you are at the UBB or a non-VBC institution (e.g. OeAW). - Basic UNIX command line experience. If you attended my command line course https://training.vbcf.ac.at/training/unix.php then you are well prepared. - Bash scripting experience is advantageous but not necessary. How to register? Make sure your supervisor agrees, and then register yourself at https://training.vbcf.ac.at/training/schedule.php#curcrs . Consult your calendar, check if you have NO OTHER COMMITMENTS. Then click on the "Register" button and fill out the little online form. Please keep in mind that a confirmed registration involves a COMMITMENT TO ATTEND. Reason: There is quite some work involved in preparing your work environment and your hands-on exercises. Plus the number of participants is limited, don't take away a slot from a colleague. See additional details at https://training.vbcf.ac.at/training/practical_information.php Thanks a lot, András VBCF Computational Biology Training Expertise Hub You are receiving this message because you are subscribed to the VBC Science mailing list. To unsubscribe from this list, go to here<https://myaccount.microsoft.com/groups/64dd6714-c5a4-4ec9-a794-e7d168bf2f88> and select "Leave". If you want to re-join at a later time, visit this link<https://myaccount.microsoft.com/groups/search> and search for "VBC List" groups to join.

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[VBC-SCIENCE] Bayesian Statistics Intro course announcement
by Aszodi,Andras May 12, 2026

May 12, 2026

Dear Colleagues, I am pleased to announce my "Bayesian statistics" course (more info at https://training.vbcf.ac.at/training/rbayes.php ). I will show you how the Bayesian paradigm fits the way we do science: starting from previous information we use observations to update our knowledge. TOPICS: - Diagnostic kits: calculating the probability of being sick if you tested positive, using Bayes' Theorem. - Life and death of a mouse: Estimating the probability parameter of the Binomial distribution. Conjugate priors, updating the posterior. - Towards modelling causality: Introduction to Bayesian Networks. OUT OF SCOPE: As usual, we cannot address specific data analysis problems relevant to your projects. Please note that this is an introductory course to a vast subject, we can cover only the basics of the basics in 4 hours. PREREQUISITES: You must be familiar with discrete and continuous distributions. If you attended my "Probability theory" course ( https://training.vbcf.ac.at/training/rprob.php ) then you are well equipped. DATE/TIME: Tuesday the 19th May, from 09:00 - 13:00. LOCATION: IMP seminar room E-016. Remote participation is offered to non-VBC colleagues and moderately sick participants. COST: free of charge. HOW TO REGISTER: 1) Check your calendar. *** If you register but don't attend, you are taking away a place from a colleague! *** 2) Ask your supervisor for permission to attend. 3) Inform your supervisor that you won't be available during the course. (No last-minute forgotten lab meetings etc! :-) ) 4) Open this URL: https://training.vbcf.ac.at/training/schedule.php Click on the [REGISTER] button and fill out the form. Please specify your job type correctly. Thank you, András You are receiving this message because you are subscribed to the VBC Science mailing list. To unsubscribe from this list, go to here<https://myaccount.microsoft.com/groups/64dd6714-c5a4-4ec9-a794-e7d168bf2f88> and select "Leave". If you want to re-join at a later time, visit this link<https://myaccount.microsoft.com/groups/search> and search for "VBC List" groups to join.

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[VBC-SCIENCE] Regular expressions course announcement
by Aszodi,Andras May 5, 2026

May 5, 2026

Dear Colleagues, Nobody likes regular expressions but they can be very useful to search for patterns in text, including nucleic acid and protein sequences. I will teach you the (well-hidden) logic behind regular expressions so that you do not have to be completely at the mercy of an LLM. Colleagues who write their own data analysis scripts are expected to benefit most. For details please visit https://training.vbcf.ac.at/training/regex.php . What? - Introduction to regular expressions. - Regular expressions with Python. - Regular expressions with R. - UNIX regular expression tools. When? Tuesday 19th May from 09:00 to 13:00. Where? IMP E-016 seminar room, physical attendance preferred. Pre-requisites: No programming experience is required to understand the basics. Most of the practical examples will be in Python, some in R and in Bash. If you know at least one of these languages then you'll be able to profit a bit more from the lecture. How much? Free of charge. How to register? Check your calendar. Make sure your PI agrees to your participation in the course. Then head to https://training.vbcf.ac.at/training/schedule.php , click on the appropriate Register button and fill out the little form. Keep in mind that registration involves a commitment to attend. See https://training.vbcf.ac.at/training/practical_information.php . Thank you, András You are receiving this message because you are subscribed to the VBC Science mailing list. To unsubscribe from this list, go to here<https://myaccount.microsoft.com/groups/64dd6714-c5a4-4ec9-a794-e7d168bf2f88> and select "Leave". If you want to re-join at a later time, visit this link<https://myaccount.microsoft.com/groups/search> and search for "VBC List" groups to join.

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[VBC-SCIENCE] Why a GLM course is good for you
by Aszodi,Andras April 29, 2026

April 29, 2026

Dear Colleagues, A few days ago I have announced a Generalised Linear Models (GLM) course with a supposedly catchy title about statistical neurodivergence. Apparently I am not good at writing catchy mails... so what can I do in this age? Ask "Claude": András: "Please formulate an explanation why molecular biology PhD students and postdocs would benefit from a course on Generalised Linear Models (GLM-s). The course discusses Binomial GLMs aka logistic regression, Poisson and Quasi-Poisson GLMs and "classical" least squares as a special case. The explanation shall be brief, appropriate for people with little time to read emails, and it should have a professional but upbeat tone as the purpose of this explanation is to motivate the target audience to sign up." This is what came back (apparently Claude read my mind and "knew" the course will use R): Claude 4.6: "If you've ever wrestled with count data, proportions, or binary outcomes in R — and forced them into a t-test or ANOVA anyway — this course is for you. Generalised Linear Models (GLMs) give you the right statistical tool for the data you actually collect in molecular biology: 🧬 Logistic regression — for binary outcomes (e.g. cell survival, mutation presence/absence) 🔢 Poisson/Quasi-Poisson GLMs — for count data (e.g. read counts, colony counts, foci per cell) 📐 Least squares as a special case — finally understand why linear regression works when it does No more shoehorning non-normal data into the wrong model. GLMs let you analyse your data honestly, report results rigorously, and hold your own in peer review. The course is hands-on, biology-focused, and designed for people who didn't sign up for a statistics degree — but need to do statistics well." If you were convinced by the LLM's sales pitch, here are some details: Date/Time: Tuesday 5th May, from 09:00 to 13:00. Mandatory pre-requisite: Good basic statistics skills. Recommended but not essential: Familiarity with least-squares regression techniques. Cost: Free of charge. How to register: First of all: If you register and then don't attend, then you take away a place from a colleague. Please plan ahead responsibly. 1) Check your calendar! 2) Ask your PI. 3) Go to the Training schedule page https://training.vbcf.ac.at/training/schedule.php , click on the "Register" button for the course and fill out the little form. Thank you, András

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[VBC-SCIENCE] Statistical Neurodivergence, or: Fitting non-Normal models
by Aszodi,Andras April 24, 2026

April 24, 2026

In our experiments we often count how many times something happened: how many mice died, how many cells got transfected, etc. Such data have non-Normal distributions and can be modelled with "generalised linear models" (GLMs), which is what this course is about. Topics: - How many mice will die of poisoning? Fitting dose-response curves with a binomial GLM (aka "logistic regression") - How many people will die of old age? Mortality rates and the Poisson GLM - The Ebola epidemic: Quasi-Poisson and negative binomial GLM - Back to the roots: Ordinary Least Squares (OLS) regression as a special case of GLM Date/Time: Tuesday 5th May, from 09:00 to 13:00. Mandatory pre-requisite: Good basic statistics skills. Recommended but not essential: Familiarity with least-squares regression techniques. Cost: Free of charge. How to register: First of all: If you register and then don't attend, then you take away a place from a colleague. Please plan ahead responsibly. 1) Check your calendar! 2) Ask your PI. 3) Go to the Training schedule page, click on the "Register" button for the course and fill out the little form. You will get an automatic acknowledgement by email, and an official confirmation from me later next week. Thanks, András

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[VBC-SCIENCE] Curve fitting course announcement
by Aszodi,Andras April 14, 2026

April 14, 2026

Dear Colleagues, "This is not my AI course", not yet. But if you want to understand neural networks, you need to learn about nonlinear regression first. TOPICS - How to fit a PCR curve? Simple nonlinear regression. - Did my enzyme inhibitor work? Statistical comparison of several nonlinear regression models. - More than one independent variable? Multivariable nonlinear regression. - Non-parametric techniques: LOESS, kernel smoothing methods, splines, generalized additive models. More details at https://training.vbcf.ac.at/training/rnonlinreg.php When? 24th April (Friday), from 09:00 to 13:00. Where? Physically at the IMP seminar room E-016. Non-VBC colleagues may attend online if needed. Mandatory prerequisites: Basic statistics knowledge: "Think Statistics! with R" course https://training.vbcf.ac.at/training/rstat.php or equivalent. Recommended: Familiarity with linear regression ( https://training.vbcf.ac.at/training/rlinreg.php ). How much? Free of charge. How to register? Check your calendar. Then head to https://training.vbcf.ac.at/training/schedule.php , click on the corresponding Register button and fill out the little form. Make sure your PI agrees to your participation. Please keep in mind that registration involves a commitment to attend. General rules: Review them carefully at https://training.vbcf.ac.at/training/practical_information.php . Best regards, András

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[VBC-SCIENCE] ANOVA course announcement
by Aszodi,Andras April 7, 2026

April 7, 2026

Dear Colleagues, In scientific research we often compare the means of groups of observations. If you have never worked with data like this: then it's just a matter of time and you definitely will :-) This is why I am offering my "ANOVA with R" course which will teach you how to analyse such datasets. TOPICS (see ANOVA course <https://training.vbcf.ac.at/training/ranova.php> for details): The intuition behind ANOVA: Comparing the means of several samples by analyzing variances. Technical details: prerequisites, omnibus F-test, post hoc tests. Getting the sample size right: Power calculations. The relationship between ANOVA and linear regression [optional]. Combination of effects: two-way ANOVA. "Are these regression lines different?" ANCOVA [if we have time]. DATE/TIME: Friday the 17th April, 09:00 - 13:00. LOCATION: "Live" at the IMP seminar room E-016 by default. Online participation via Zoom is available only as a fallback option. PREREQUISITES: Familiarity with R and basic statistics knowledge. Attending my Linear Regression course <https://training.vbcf.ac.at/training/rlinreg.php> which is scheduled on Thursday 16th April is highly recommended as the two methodologies are intimately related. COST: Free of charge. HOW TO REGISTER: First of all: If you register and then don't attend, then you take away a place from a colleague. Please plan ahead responsibly. 1) Check your calendar! 2) Ask your PI. 3) Go to the Training schedule <https://training.vbcf.ac.at/training/schedule.php> page, click on the "Register" button for the ANOVA course and fill out the little form. Note that the linear regression course registration is still open, please do not mix up the two! (But it's all right to attend both... :-) ) You will get an automatic acknowledgement by email, and an official confirmation from me later this week. Thanks, András

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[VBC-SCIENCE] Linear regression course announcement
by Aszodi,Andras April 1, 2026

April 1, 2026

Dear Colleagues, * The "LLM Castle of AI" (vibe-painted by me personally, with Mr Claude's help) is based on transformer networks. * Transformer networks are neural networks. * Neural networks are nonlinear regression methods. * Nonlinear regression is based on linear regression. This means that linear regression is the cellar of the "AI castle". Join me in exploring this cellar, which harbours no monsters or expensive wine, but some interesting topics, such as: - How to fit straight lines? Single, weighted and multivariable linear regression. - How to model noise in both variables? Orthogonal regression, Principal Components Analysis. - How to simplify the models? LASSO, Ridge, Elastic Net regressions. - What to do with correlated independent variables? Principal component regression, orthogonal polynomial regression. More details at https://training.vbcf.ac.at/training/rlinreg.php WHEN? 16th April (Thursday), from 09:00 to 13:00. WHERE? Physically at the IMP seminar room E-016. Non-VBC colleagues may attend online if needed. PREREQUISITES: Basic statistics knowledge. If you have attended my "Think Statistics! with R" course ( https://training.vbcf.ac.at/training/rstat.php ) then you are well prepared. Some very basic familiarity with R is also required. HOW MUCH? Free of charge. HOW TO REGISTER? Check your calendar. Then head to https://training.vbcf.ac.at/training/schedule.php , click on the corresponding Register button and fill out the little form. Make sure your PI agrees to your participation in the course. Please keep in mind that registration involves a commitment to attend. GENERAL RULES: Review them carefully at https://training.vbcf.ac.at/training/practical_information.php . Best regards, András

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[VBC-SCIENCE] Visualisiation with ggplot course announcement
by Aszodi,Andras March 17, 2026

March 17, 2026

Dear Colleagues, I have the pleasure to announce my "Scientific Visualisation with ggplot" course. The aim of this course is to teach you how to create informative scientific plots using the ggplot package in R. For more details see https://training.vbcf.ac.at/training/rggplot.php . WHEN? Thursday the 26th March, from 09:00 to 13:00. WHERE? In person by default, in the IMP seminar room E-016. If you get (moderately) sick, you may participate online via Zoom, no need to cancel your participation. WHAT? • Fundamentals of scientific visualisation (this is not ggplot-specific but very useful). • Introduction to ggplot. Data preparation, plot creation workflow. • ggplot details: bars, boxes, densities, function plots, faceting (subplots). PREREQUISITES: Basic familiarity with R. Having attended my R language course ( https://training.vbcf.ac.at/training/rlang.php ) is an advantage. HOW MUCH? Free of charge. HOW TO REGISTER: First of all: If you register and then don't attend, then you take away a place from a colleague. Please plan ahead responsibly. 1) Check your calendar! 2) Ask your PI. 3) Go to the Training schedule page, click on the "Register" button for the ggplot course and fill out the little form. You will get an automatic acknowledgement by email, and an official confirmation from me later this week. NUMBER OF PARTICIPANTS: Limited to 12 in-person participants due to seminar room size. But I will organise an "overflow" course if needed. GENERAL RULES: please review them carefully at https://training.vbcf.ac.at/training/practical_information.php . Best regards, András You are receiving this message because you are subscribed to the VBC Science mailing list. To unsubscribe from this list, go to here<https://myaccount.microsoft.com/groups/64dd6714-c5a4-4ec9-a794-e7d168bf2f88> and select "Leave". If you want to re-join at a later time, visit this link<https://myaccount.microsoft.com/groups/search> and search for "VBC List" groups to join.

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[VBC-SCIENCE] Clustering and Classification course announcement
by Aszodi,Andras March 9, 2026

March 9, 2026

Dear Colleagues, I have the pleasure to announce a refurbished and extended "Clustering and Classification with Python" course, part of my "machine learning"/"advanced statistical modelling" collection. The course provides a short introduction to the huge subject of clustering and classifying observations. We will apply these tools e.g. to discriminate between healthy and diseased states based on example genomic datasets. For more details visit https://training.vbcf.ac.at/training/pyclassif.php . Topics: - Hierarchical clustering, k-means clustering. - Gaussian mixtures, E-M algorithm. - Quadratic and linear discriminant analysis. - Principal Components Analysis (PCA). - Cross-validation techniques. - Logistic regression and its connection with discriminant analysis. Multinomial regression. Out of scope: We can cover only basic methodologies. I have no resources to discuss analysis of private data sets during the course. When? Two half-days on the 19th and 20th March (Thu-Fri), from 09:00 to 13:00 on both days. Where? IMP seminar room E-016. Pre-requisites: - Proficiency in Python. https://training.vbcf.ac.at/training/pylang.php - Familiarity with NumPy, Pandas (https://training.vbcf.ac.at/training/pydata.php) and a little bit of MatPlotLib. - Solid probability theory and statistics knowledge. - Knowledge of basic linear algebra concepts: vectors, matrices etc. Cost: Free of charge. How to register? Make sure you don't have any meetings on the days of the course. Then ask your boss for permission to attend, and sign up at https://training.vbcf.ac.at/training/schedule.php by filling out the little form. Sign up only if you are confident that you will attend, don't take away a slot from a colleague. Consult the general attendance rules at https://training.vbcf.ac.at/training/practical_information.php . You will get a confirmation from me later this week. Thank you, András

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