Please note: This instance is for testing/development, and any content submitted may be changed or deleted without warning.
Training eSupport System
  • Log In
    • Login
    • Register
  • About
  • Events
  • Materials
  • e-Learning
  • Workflows
  • Collections
  • Learning paths
  • Directory
    • Trainers
    • Providers
    • Nodes

TeSS makes use of some necessary cookies to provide its core functionality.

See our Privacy Policy for more information.

You can modify your cookie preferences at any time here, or from the link in the footer.

Allow necessary cookies
  1. Home
  2. Materials

Filter

  • Sort

  • Filter Clear filters

    • Scientific topic
    • Markov processes
    • Biological sequences16
    • Sequence analysis16
    • Sequence databases16
    • Community analysis13
    • Environmental microbiology13
    • Microbial ecology13
    • Microbiome13
    • Molecular community analysis13
    • Antimicrobial stewardship12
    • Exomes12
    • Genome annotation12
    • Genomes12
    • Genomics12
    • Medical microbiology12
    • Metagenomics12
    • Microbial genetics12
    • Microbial physiology12
    • Microbial surveillance12
    • Microbiological surveillance12
    • Microbiology12
    • Molecular infection biology12
    • Molecular microbiology12
    • Personal genomics12
    • Shotgun metagenomics12
    • Synthetic genomics12
    • Viral genomics12
    • Whole genomes12
    • Taxonomy9
    • Algorithms6
    • Bayesian methods6
    • Biostatistics6
    • Computer programming6
    • Data structures6
    • De novo genome sequencing6
    • Descriptive statistics6
    • Gaussian processes6
    • Genome sequencing6
    • Inferential statistics6
    • Multivariate statistics6
    • Probabilistic graphical model6
    • Probability6
    • Programming languages6
    • Software development6
    • Software engineering6
    • Statistics6
    • Statistics and probability6
    • WGS6
    • Whole genome resequencing6
    • Whole genome sequencing6
    • Assembly4
    • DNA metabarcoding4
    • Environmental metabarcoding4
    • Epidemiology4
    • Metabarcoding4
    • Public health4
    • Public health and epidemiology4
    • RNA metabarcoding4
    • Sequence assembly4
    • eDNA metabarcoding4
    • eRNA metabarcoding4
    • Comparative transcriptomics3
    • Computational ecology3
    • Ecoinformatics3
    • Ecological informatics3
    • Ecology3
    • Ecosystem science3
    • Mobile genetic elements3
    • Transcriptome3
    • Transcriptomics3
    • Transposons3
    • AMR2
    • Antibiotic resistance (ABR)2
    • Antifungal resistance2
    • Antimicrobial resistance2
    • Antiprotozoal resistance2
    • Antiviral resistance2
    • DNA variation2
    • Epigenomics2
    • Extensive drug resistance (XDR)2
    • Function analysis2
    • Functional analysis2
    • Genetic variation2
    • Genomic variation2
    • Metatranscriptomics2
    • Multidrug resistance2
    • Multiple drug resistance (MDR)2
    • Multiresistance2
    • Mutation2
    • Pandrug resistance (PDR)2
    • Polymorphism2
    • Protein function analysis2
    • Protein function prediction2
    • Somatic mutations2
    • Total drug resistance (TDR)2
    • Communicable disease1
    • Disease1
    • Evolution1
    • Evolutionary biology1
    • Functional genomics1
    • Show N_FILTERS more
    • Tool
    • Galaxy1
    • scikit-learn1
    • Show N_FILTERS more
    • Content provider
    • Galaxy Training6
    • Show N_FILTERS more
    • Keyword
    • Statistics and machine learning6
    • Large Language Model5
    • ai-ml5
    • elixir5
    • jupyter-notebook5
    • work-in-progress1
    • Show N_FILTERS more
    • Difficulty level
    • Intermediate5
    • Beginner1
    • Show N_FILTERS more
    • Licence
    • Creative Commons Attribution 4.0 International6
    • Show N_FILTERS more
    • Target audience
    • Students6
    • Show N_FILTERS more
    • Author
    • Bérénice Batut
    • Anup Kumar9
    • Raphael Mourad6
    • Alireza Khanteymoori4
    • Kaivan Kamali4
    • Daniel Blankenberg2
    • Fabio Cumbo2
    • Fotis E. Psomopoulos2
    • Janick Mathys2
    • Ralf Gabriels2
    • Simon Bray2
    • Daniela Schneider1
    • Dennis Lal group1
    • Ekaterina Polkh1
    • Marie Gramm1
    • Marzia A Cremona1
    • Stella Fragkouli1
    • Vijay1
    • Wandrille Duchemin1
    • Show N_FILTERS more
    • Contributor
    • Björn Grüning6
    • Bérénice Batut6
    • Anup Kumar5
    • olisand5
    • Wandrille Duchemin4
    • Alireza Khanteymoori1
    • Armin Dadras1
    • Helena Rasche1
    • Martin Čech1
    • Saskia Hiltemann1
    • Show N_FILTERS more
    • Resource type
    • e-learning
    • Show N_FILTERS more
    • Related resource
    • Jupyter Notebook (with Solutions)5
    • Jupyter Notebook (without Solutions)5
    • Associated Training Datasets1
    • Associated Workflows1
    • Show N_FILTERS more
  • Show disabled materials
  • Show archived materials
    • Date added
    • In the last 24 hours
    • In the last 1 week
    • In the last 1 month

e-Learning

  • Subscribe via email

Email Subscription

Register training material

Scientific topics: Markov processes

and Authors: Bérénice Batut

and Resource type: e-learning

6 e-learning materials found
  • e-learning

    Fine-tuning a LLM for DNA Sequence Classification

    •• intermediate
    Statistics and probability Large Language Model Statistics and machine learning ai-ml elixir jupyter-notebook
  • e-learning

    Pretraining a Large Language Model (LLM) from Scratch on DNA Sequences

    •• intermediate
    Statistics and probability Large Language Model Statistics and machine learning ai-ml elixir jupyter-notebook
  • e-learning

    Predicting Mutation Impact with Zero-shot Learning using a pretrained DNA LLM

    •• intermediate
    Statistics and probability Large Language Model Statistics and machine learning ai-ml elixir jupyter-notebook
  • e-learning

    Optimizing DNA Sequences for Biological Functions using a DNA LLM

    •• intermediate
    Statistics and probability Large Language Model Statistics and machine learning ai-ml elixir jupyter-notebook work-in-progress
  • e-learning

    Generating Artificial Yeast DNA Sequences using a DNA LLM

    •• intermediate
    Statistics and probability Large Language Model Statistics and machine learning ai-ml elixir jupyter-notebook
  • e-learning

    Machine learning: classification and regression

    • beginner
    Statistics and probability Statistics and machine learning
Training eSupport System
contact@example.com
Contribute
About TeSS
Funding & acknowledgements
Privacy
Cookie preferences
Version: 1.5.0
Source code
API documentation
Bioschemas testing tool

TeSS has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 676559.