Logo.tif
P1150571
P1150571

press to zoom
IMG_20220520_092856
IMG_20220520_092856

press to zoom
Imagem2
Imagem2

press to zoom
P1150571
P1150571

press to zoom
1/9

International School of Chemometrics - 2023
ISC - 2023

NOTE: All seminars include all the material that the student might need: 

- Slides of the course (pdf).

- Exercises

- Datasets

- Toolboxes

- Refreshments during the lessons (coffee, tea, candies, cookies, and other amenities). This, of course, if we are allowed due to the Covid-19 pandemic situation

- We do NOT provide: Matlab and lunch

SEMINAR 1 - PROGRAMMING

Introduction to Programming (Matlab, R and Python) for Multivariate Data Analysis

 

Since the very beginning, the ISC has always counted with a first week of Introduction to Matlab for Multivariate Data Analysis. It was a week that worked very well. We wanted to create something special. We have had many requests regarding Python and R. Therefore, we have decided to create a new module that includes the three major languages!

 

How does it work?

- Due to time constraints, The lessons will be online with pre-recorded videos.

- The topics will be:

1) Language structure; 2) vectors and matrices; 3) arrays; 4) Basic operations; 5) Graphical Output, beginning; 6) Data structures and datasets; 7) Loops; 8) Conditions; 9) Another tricks in control flow; 10) Functions; 11) Data preprocessing; 12) Principal Component Analysis; 13) Graphical Output, advanced; 14) Images. We are planning between 4 - 6 hours of recordings per language.

- They are three simultaneous courses. One per language, BUT:

1) The student will have access to ALL THE MATERIAL AND VIDEOS for the three courses. It is up to the student which language to follow.

2) ALL THE EXACT SAME MATERIAL (examples, exercises, etc) will be reproduced in the three languages.

- The videos and material will be released on the 25th of April, 2022, and they will stay available until the end of October 2022. Only the students who signed up officially will have access to the videos and material. It is REALLY ADVISABLE that the students run the material and practice during the week from the 25th until the 30th of April. During that period, we will create a consultancy platform where the teachers will be available to answer your questions and doubts.

Dates and timetable: 29th of May - 3th of June. 

 

Previous knowledge needed: None

Software needed: Matlab, R, Python

Teachers: José Manuel Amigo (Matlab), Sergey Kucheryavskyi (R), Anders Krogh Mortensen (Phyton).

ECTS: 1

Prices:

- University members: 600 DKK (The payment is made in Danish Krona - DKK - Approx. 81 euro / 98 USD)

- Industry/Private company: 1500 DKK (The payment is made in Danish Krona - DKK - Approx. 200 euro / 245 USD)

 

SEMINAR 2 - BASIC

A basic introduction to Chemometrics, data types, data pre-processing, PCA, Multivariate Linear Regression, and Linear Algebra

 

This seminar contains two general topics:

 

- EXPLORE - Data exploration and regression: Principal Component Analysis has become the most powerful and versatile tool for exploring data tables in Analytical Sciences. Here we present a course to show the main benefits and drawbacks of PCA when it is used for different kinds of analytical data: Spectroscopy, environmental assessment, sensory, experiments performance, chromatography, etc. Moreover, preprocessing of different types of data will also be addressed in the seminar as a prerequisite for having the optimal possibility for exploring the data. If PCA is the keystone of pattern recognition methods, PLS is the keystone of multivariate calibration methods. This seminar will give a general overview of different multivariate calibration strategies (Multilinear Regression, Principal Component Regression), and will focus on Partial Least Squares regression.

- LINAL - Linear Algebra: The Foundation for chemometric modeling is Linear Algebra. Why do the algorithms work? Why are the models meaningful? A math-derived answer to these questions can be found using linear algebra. The seminar will focus on hands-on experience with some fundamental linear algebra concepts, including rank, determinant, inverse, pseudo inverse, eigenvalues, singular value decomposition, orthogonality and basis sets. We will analyze a few real-life datasets, but the purpose of the seminar is to be a proficient mechanic unraveling the black box of algorithms and models, while other courses will learn you how to drive the car. 

Dates and timetable: From the 5th of June until the 9th of June, 2023. From 9 am until 4 pm (CET) with a 1-hour lunch break (30 hours)

 

Previous knowledge needed: None

 

Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

Matlab

- PLS_Toolbox / SOLO. IMPORTANT: For the PLS_Toolbox / SOLO, a fully functional demo will be available for the School.

Teachers: José Manuel Amigo (EXPLORE) and Morten A. Rasmussen (LINAL).

ECTS: 2.5

Prices:

- University members: 1500 DKK (The payment is made in Danish Krona - DKK - Approx. 200 euro / 245 USD)

- Industry/Private company: 3750 DKK (The payment is made in Danish Krona - DKK - Approx. 505 euro / 612 USD)

SEMINAR 3 - INTERMEDIATE

Intermediate topics on Chemometrics. Linear Classification, Variable selection methods, Multivariate Curve Resolution

This seminar contains three general topics:

 

- CLASS - Multivariate Classification: The course will deal with the main linear classification methods. We will initially introduce what classification is and a bit of terminology, such as the difference between class modeling and discriminant methods, classification measures, and validation approaches. Then, we will move to the main classification methods, such as Discriminant Analysis, Partial Least Squares Discriminant Analysis (PLS-DA) and SIMCA. We will see both theoretical aspects and practical applications. There will be practical sessions where we will apply classification methods to real data with ad-hoc toolboxes in MATLAB.to learn how to handle these tasks.

- VARSEL - Variable selection methods: In this one-day hands-on course on variable selection, you will become familiar with state-of-the-art variable selection. This will cover both classical, iterative, model-based and nature-inspired algorithms. I will also give you some pros and cons of the different methods, and some suggestions for how to operate them even better. The cases you will be working with can be done in R, Matlab (w/ wo PLS-toolbox) or python, all as you see fit. However, I only provide the necessary toolboxes for Matlab.

- MCR - Multivariate Curve Resolution: The module will address the theoretical description and hands-on application of Multivariate Curve Resolution (MCR). MCR is a multivariate resolution (unmixing) method that can provide the description of a multicomponent data set through a bilinear model of chemically meaningful profiles, e.g., when analyzing an HPLC-DAD data set, MCR would provide the real elution profiles and the related UV spectra for each compound in the sample. It has applications in diverse fields, such as process analysis, chromatographic data, hyperspectral images or environmental data, in any context where a mixture analysis problem can be encountered. MCR can be applied to a single data matrix or to multiset structures formed by blocks of different information (data fusion). The module focuses mainly on the algorithm MCR-ALS (Multivariate Curve Resolution-Alternating Least Squares), and hands-on work will be done using a dedicated free GUI interface adapted to MATLAB environment. Applications will cover many of the areas mentioned above.

Dates and timetable: From the 12th until the 16th of June, 2023. From 9 am until 4 pm (CET) with 1-hour lunch break (30 hours)

 

Previous knowledge needed: Basic multivariate data analysis and Matlab

Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

Matlab

The Classification toolbox can be freely downloaded from here: https://michem.unimib.it/download/matlab-toolboxes/classification-toolbox-for-matlab/

- PLS_Toolbox / SOLO. IMPORTANT: For the PLS_Toolbox / SOLO, a fully functional demo will be available for the School.

- MCR-ALS toolbox: MCR-ALS toolbox can be freely downloaded here: https://mcrals.wordpress.com/download/mcr-als-2-0-toolbox/

Teachers: Davide Ballabio (CLASS), Asmund Rinnan (VARSEL), Anna de Juan (MCR).

ECTS: 2.5

Prices:

- University members: 1500 DKK (The payment is made in Danish Krona - DKK - Approx. 200 euro / 245 USD)

- Industry/Private company: 3750 DKK (The payment is made in Danish Krona - DKK - Approx. 505 euro / 612 USD)

CHALLENGES

This week is composed of different and individual seminars for a further understanding of more and extremely useful analytical methods. Some of them are on the same dates. So please, verify the dates to avoid overlapping.

 

SEMINAR 4 - DL

Non-Linear Modeling and Deep Learning.

This seminar aims at providing a basic introduction to the techniques which may be used in all those situations when a linear relation is not enough to provide accurate results (e.g. due to the presence of multiple sources of variability). In this respect, the most important aspects of data modeling will be considered (exploratory analysis, classification and calibration). Topics such as kernel and dissimilarity-based approaches (including support vector machines), local modeling (kNN and locally weighted regression/classification), and different artificial neural network architectures (shallow learning and deep learning) will be covered. 

Dates and timetable: From the 19th until the 21st of June, 2023. From 9 am until 4 pm (CET) with 1-hour lunch break (30 hours)

 

Previous knowledge needed: Basic multivariate data analysis

Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

Matlab and Python

- PLS_Toolbox / SOLO. IMPORTANT: For the PLS_Toolbox / SOLO, a fully functional demo will be available for the School.

- Deep Learning Toolbox of Matlab

Teachers: Rasmus Bro (19th of June) and Jesper Løve Hinrich (20th and 21st of June).

ECTS: 1.5

Prices:

- University members: 900 DKK (The payment is made in Danish Krona - DKK - Approx. 120 euro / 120 USD)

- Industry/Private company: 2250 DKK (The payment is made in Danish Krona - DKK - Approx. 300 euro / 300 USD)

SEMINAR 5 - DoE

Design of Experiments.

TBD

Dates and timetable: From the 19th until the 20th of June, 2023. From 9 am until 4 pm (CET) with 1-hour lunch break (12 hours)

 

Previous knowledge needed: Basic multivariate data analysis

Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

Teacher: Agnieszka Smolinska

ECTS: 1

Prices:

- University members: 600 DKK (The payment is made in Danish Krona - DKK - Approx. 81 euro / 81 USD)

- Industry/Private company: 1500 DKK (The payment is made in Danish Krona - DKK - Approx. 200 euro / 200 USD)

SEMINAR 6 - ASCA

ANOVA - Simultaneous Component Analysis.

Anova Simultaneous Component Analysis (ASCA) is a versatile tool for analyzing multivariate data from designed experiments. Based on ANOVA variance partitioning followed by bi-linear modeling of the individual effect matrices, the method offers detailed insight into small systematic variance contributors that otherwise are masked and uncovered by traditional techniques such as PCA. This workshop will uncover the basic principles in ASCA and give the attendees hands-on experience on using the tool on real data using the PLStoolbox in Matlab® as well as on its own.

Dates and timetable: 21st of June, 2023. From 9 am until 4 pm (CET) with 1-hour lunch break (6 hours)

 

Previous knowledge needed: Basic multivariate data analysis

Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

Matlab

- PLS_Toolbox / SOLO. IMPORTANT: For the PLS_Toolbox / SOLO, a fully functional demo will be available for the School.

Teacher: Morten A. Rasmussen

ECTS: 0.5

Prices:

- University members: 300 DKK (The payment is made in Danish Krona - DKK - Approx. 40 euro / 40 USD)

- Industry/Private company: 750 DKK (The payment is made in Danish Krona - DKK - Approx. 100 euro / 100 USD)

SEMINAR 7 - MW

Multi Way analysis

Multi-way data is gaining popularity due to the capability of scientific devices to generate data with, at least, 3 dimensions (elution time – mz channel – samples, excitation-emission – sample, etc). Therefore, learning the basics of multi-way analysis will help to extract the most of that complex data structure. In this sense, methods like parallel factor analysis (PARAFAC) and PARAFAC2 will be studied and applied to different examples.

Dates and timetable: 22nd of June, 2023. From 9 am until 4 pm (CET) with 1-hour lunch break (6 hours)

 

Previous knowledge needed: Basic multivariate data analysis

Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

Matlab

- PLS_Toolbox / SOLO. IMPORTANT: For the PLS_Toolbox / SOLO, a fully functional demo will be available for the School.

Teacher: Rasmus Bro

ECTS: 0.5

Prices:

- University members: 300 DKK (The payment is made in Danish Krona - DKK - Approx. 40 euro / 40 USD)

- Industry/Private company: 750 DKK (The payment is made in Danish Krona - DKK - Approx. 100 euro / 100 USD)

SEMINAR 8 - DF

Data Fusion

The seminar will deal with the chemometric approaches for integrating (“fusing”) data from different sources. First of all, the various configurations which may occur when dealing with multiple data matrices will be presented and discussed, and a hierarchy/systematization of the possible data fusion approaches will be introduced. Then the main multi-block strategies for data exploration and predictive modeling will be discussed and compared, and further classification of models depending on whether the globally common, locally common and distinct information is considered or not will be introduced. The theoretical and algorithmic description of the methods will be accompanied by worked examples of real data sets.

Dates and timetable: 22nd of June, 2023. From 9 am until 4 pm (CET) with 1-hour lunch break (6 hours)

 

Previous knowledge needed: Basic multivariate data analysis

Software needed: Feel free to work with Matlab, Python or R, or any other software that you consider (e.g. Unscrambler). The teachers will work with:

Matlab

Teacher: Federico Marini

ECTS: 0.5

Prices:

- University members: 300 DKK (The payment is made in Danish Krona - DKK - Approx. 40 euro / 40 USD)

- Industry/Private company: 750 DKK (The payment is made in Danish Krona - DKK - Approx. 100 euro / 100 USD)

SEMINAR 9 - GLUE (How not to make Chemometrics) and WORKSHOP

This seminar is divided into two parts:

- Morning: We will take a very close look at all the most common mistakes that even experienced people will do when doing multivariate analysis. We will cover exploration, calibration, interpretation, visualization and many other subjects. And always with a focus on what is the most common problem as well as a sounder alternative.

- Afternoon: Any student of the School will be able to ask whatever question remaining from any seminar. Also, there will be time to work on your own data and check with us on the analysis workflow.

 

Dates and timetable: 23rd June, 2023. From 9 am until 4 pm (CET) with 1-hour lunch break (6 hours)

Previous knowledge needed: Chemometrics

Software: Up to you!

Teacher: José Manuel Amigo, Rasmus Bro and Federico Marini

ECTS: 0

Price: 0 DKK (Approx. 0 euro / 0 USD)

If you are interested or have any question, please, write an email to:

ischemometricshelp@gmail.com