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Regular version of the site

Laboratory on AI for Computational Biology

Publications
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. P. 5068.

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). We are also hiring a C++ programmer! For more info contact Attila Kertesz-Farkas by email.


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"

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.

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

Illustration for news: 'The Efforts Taken by HSE University to Make My Internship Format Online Are Laudable'

'The Efforts Taken by HSE University to Make My Internship Format Online Are Laudable'

John Hopkins graduate Kayode Ahmed is interning at the Faculty. We talked to him about his career path, internship project, and hobbies.

Illustration for news: Attila Kertesz-Farkas about New Lab and Research

Attila Kertesz-Farkas about New Lab and Research

Laboratory on AI for Computational Biology has opened at the Faculty not so long ago. We talked with its head, Attila Kertesz-Farkas, about the lab, research and his way in science.

Illustration for news: Seminar: "Introduction to computational mass spectrometry"

Seminar: "Introduction to computational mass spectrometry"