• Alimova I, Tutubalina E, Nikolenko S.I., Cross-domain Limitations of Neural Models on Biomedical Relation Classification//IEEE Access. - 2021. - Vol., Is.. - .
• Tutubalina E, Alimova I, Miftahutdinov Z, The Russian Drug Reaction Corpus and neural models for drug reactions and effectiveness detection in user reviews//Bioinformatics (Oxford, England). - 2021. - Vol.37, Is.2. - P.243-249.
• Magge A, Tutubalina E, Miftahutdinov Z, DeepADEMiner: a deep learning pharmacovigilance pipeline for extraction and normalization of adverse drug event mentions on Twitter//Journal of the American Medical Informatics Association : JAMIA. - 2021. - Vol.28, Is.10. - P.2184-2192.

• Alimova I, Tutubalina E., Multiple features for clinical relation extraction: A machine learning approach//Journal of Biomedical Informatics. - 2020. - Vol.103, Is.. - Art. № 103382.
• Alimova I, Tutubalina E, Kirillovich A., Cross-lingual transfer learning for semantic role labeling in russian//Proceedings of the International Conference Computational Linguistics in Bulgaria. - 2020. - Vol., Is.. - P.72-80.
• Miftahutdinov Z, Alimova I, Tutubalina E., On biomedical named entity recognition: Experiments in interlingual transfer for clinical and social media texts//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2020. - Vol.12036 LNCS, Is.. - P.281-288.

• Khasianov, A., Alimova, I., Marchenko, A., Nurhambetova, G., Tutubalina, E., Zuev, D. Lawyer's Intellectual Tool for Analysis of Legal Documents in Russian//Proceedings - 2018 International Conference on Artificial Intelligence: Applications and Innovations, IC-AIAI 2018. - 2019. - Vol., Is.. - P.42-46.
• Miftakhutdinov Zulfat, Alimova Ilseyar, Tutubalina Elena, KFU NLP Team at SMM4H 2019 Tasks: Want to Extract Adverse Drugs Reactions from Tweets? BERT to The Rescue//SOCIAL MEDIA MINING FOR HEALTH APPLICATIONS (#SMM4H) WORKSHOP & SHARED TASK. - 2019. - Vol., Is.. - P.52-57.
• Alimova I.S, Tutubalina E.V., Entity-Level Classification of Adverse Drug Reaction: A Comparative Analysis of Neural Network Models//Programming and Computer Software. - 2019. - Vol.45, Is.8. - P.439-447.
• Alimova I, Tutubalina E., Comparative analysis of context representation models in the relation extraction task from biomedical texts//CEUR Workshop Proceedings. - 2019. - Vol.2525, Is.. - .

• Alimova I, Tutubalina E., Automated detection of adverse drug reactions from social media posts with machine learning//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 2018. - Vol.10716 LNCS, Is.. - P.3-15.
  Automated_Detection_of_Adverse_Drug_Reactions_From_Social_Media_Posts_With_Machine_Learning.pdf
• Nugmanov R., Tutubalina E., Miftahutdinov Z., Exploring semantic analysis of biomedical texts for identification of drugs with similar therapeutic effects//EUROPEAN JOURNAL OF CLINICAL INVESTIGATION. - 2018. - Vol.48, Is.. - P.217-217.
• Nugmanov R., Alimova I., Tutubalina E., Detecting adverse drug reactions from user reviews with machine learning//EUROPEAN JOURNAL OF CLINICAL INVESTIGATION. - 2018. - Vol.48, Is.. - P.217-218.
• Alimova I, Solovyev V., Interactive attention network for adverse drug reaction classification//Communications in Computer and Information Science. - 2018. - Vol.930, Is.. - P.185-196.

• Е. В. Тутубалина, З. Ш. Мифтахутдинов, Р. И. Нугманов, Т. И. Маджидов, С. И. Николенко, И. С. Алимова, А. Э. Тропша. Идентификация лекарственных средств со схожим терапевтическим действием на основе семантического анализа текстов //Известия академии наук. Серия химическая. — 2017. — № 11.
  IAN2180.pdf
• Alimova Ilseyar, Tutubalina Elena, Alferova Julia, A Machine Learning Approach to Classification of Drug Reviews in Russian//2017 IVANNIKOV ISPRAS OPEN CONFERENCE (ISPRAS). - 2017. - Vol., Is.. - P.64-69.
  F_A_Machine_Learning_Approach_to_Classification_of_Drug_Reviews_in_Russian.pdf
• Tutubalina E.V, Miftahutdinov Z.S, Nugmanov R.I, Using semantic analysis of texts for the identification of drugs with similar therapeutic effects//Russian Chemical Bulletin. - 2017. - Vol.66, Is.11. - P.2180-2189.

• Сравнительный анализ мер сходства, основанных на преобразовании скользящих аппроксимаций, в задачах классификации временных рядов. Труды первой научно-практической Открытой конференции ИСП РАН, 1-2 декабря 2016 г.

• Ivanov V.V, Tutubalina E.V, Mingazov N.R, Extracting aspects, sentiment and categories of aspects in user reviews about restaurants and cars//Komp'juternaja Lingvistika i Intellektual'nye Tehnologii. - 2015. - Vol.2, Is.14. - P.22-33.