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Regular version of the site

Laboratory on AI for Computational Biology

Publications
Article
Nucleus segmentation: towards automated solutions
In press

Hollandi R., Moshkov N., Paavolainen L. et al.

Trends in Cell Biology. 2022.

Article
Local ancestry prediction with PyLAE

Moshkov N., Smetanin A., Tatarinova T.

PeerJ. 2021.

Article
Deep Convolutional Neural Networks Help Scoring Tandem Mass Spectrometry Data in Database-Searching Approaches

Kudriavtseva P., Kashkinov M., Kertész-Farkas A.

Journal of Proteome Research. 2021. Vol. 20. No. 10. P. 4708-4717.

Article
SpheroidPicker for automated 3D cell culture manipulation using deep learning

Grexa I., Diosdi A., Harmati M. et al.

Scientific Reports. 2021. Vol. 11.

Article
Annotation of tandem mass spectrometry data using stochastic neural networks in shotgun proteomics

Sulimov P., Voronkova A. V., Kertész-Farkas A.

Bioinformatics. 2020. Vol. 36. No. 12. P. 3781-3787.

Article
Test-time augmentation for deep learning-based cell segmentation on microscopy images

Moshkov N., Mathe B., Kertesz-Farkas A. et al.

Scientific Reports. 2020. Vol. 10.

About the Laboratory

Welcome to the AIC Lab. We create cutting-edge deep learning technologies for biomolecular medical data analysis to be used in life sciences and biomedical applications. We are an international, English-speaking, multidisciplinary group with a background in computer science, math, and molecular biology.

Join the English-speaking AIC Lab and gain hands on experience with high-performance computing technologies, statistical testing methods, and deep learning methods applied on interesting real-life applications. Research projects are available at any levels (BSC, MSc, PhD, Post-doc, summer practice, and summer internships). 


Illustration for news: Attila Kertes-Farkas received the best award for his presentation at IMLC 2023 conference

Attila Kertes-Farkas received the best award for his presentation at IMLC 2023 conference

The head of AIC Laboratory, Attila Kertes-Farkas, was awarded for the best presentation at the ICMLC 2023 conference.

Illustration for news: Congratulations to the Head of Laboratory on AI for Computational Biology Kertesz-Farkas Attila on receiving the well-deserved award

Congratulations to the Head of Laboratory on AI for Computational Biology Kertesz-Farkas Attila on receiving the well-deserved award

The head of the laboratory is presented for the award.

Illustration for news: International seminar "Light scattering techniques – versatile tools to study nanoparticle dispersions"

International seminar "Light scattering techniques – versatile tools to study nanoparticle dispersions"

An international seminar was held jointly with the University of Szeged.

Illustration for news: Attila Kertesz-Farkas successfully defended Doctoral Thesis

Attila Kertesz-Farkas successfully defended Doctoral Thesis

On May 19th, 2022, Attila Kertesz-Farkas defended the doctoral thesis.

Illustration for news: Attila Kertesz-Farkas had a talk on FCS's Colloquium meeting

Attila Kertesz-Farkas had a talk on FCS's Colloquium meeting

 AIC LAB Head had a talk at traditional colloquium.

Illustration for news: AIC LAB wish you Merry Christmas and Happy New Year

AIC LAB wish you Merry Christmas and Happy New Year

Merry Christmas!

Illustration for news: Seminar "Neuro-Symbolic approaches in Visual Question Answering problems"

Seminar "Neuro-Symbolic approaches in Visual Question Answering problems"

The next workshop of the laboratory took place.

Illustration for news: Seminar "Computational methods for tandem mass spectrometry data annotation"

Seminar "Computational methods for tandem mass spectrometry data annotation"

On November 26, 2021 an online seminar was held on the results of a study by the head of the laboratory Attila Kertesz-Farkas.

Illustration for news: Seminar "Deep Convolutional Neural Networks Help Scoring Tandem Mass Spectrometry Data in Database-Searching Approaches"

Seminar "Deep Convolutional Neural Networks Help Scoring Tandem Mass Spectrometry Data in Database-Searching Approaches"

A workshop of the laboratory was held.

Illustration for news: Researchers Discover How to Obtain ‘Ideal’ 3D Cell Cultures for Cancer Research

Researchers Discover How to Obtain ‘Ideal’ 3D Cell Cultures for Cancer Research

A group of scientists from Hungary, Russia and Finland have developed a system capable of selecting cancer cells of a specific shape and size—spheroids. SpheroidPicker, the first AI device of its kind, enables a more standardized approach to working with tumour samples. The results of the research have been published in the journal Scientific Reports. One of researchers who worked on the project is Nikita Moshkov, Junior Research Fellow of the Laboratory on AI for Computational Biology.