Biology subjects

Hakobyan, A.

Publications and source records attributed to Hakobyan, A..

3 recordsLinked to original sources

bioRxiv2024

Multimodal learning of transcriptomes and text enables interactive single-cell RNA-seq data exploration with natural-language chats

Single-cell RNA-seq characterizes biological samples at unprecedented scale and detail, but data interpretation remains challenging. Here we introduce CellWhisperer, a multimodal machine learning model and software that connects transcriptomes and text for interactive single-cell RNA-seq data analysis. CellWhisperer enables the chat-based interrogation of transcriptome data in English language. To train our model, we created an AI-curated dataset with over a million pairs of RNA-seq profiles and matched textual annotations across a broad range of human biology, and we established a multimodal embedding of matched transcriptomes and text using contrastive learning. Our model enables free-text search and annotation of transcriptome datasets by cell types, states, and other properties in a zero-shot manner and without the need for reference datasets. Moreover, Cell-Whisperer answers questions about cells and genes in natural-language chats, using a biologically fluent large language model that we fine-tuned to analyze bulk and single-cell transcriptome data across various biological applications. We integrated CellWhisperer with the widely used CELLxGENE browser, allowing users to in-teractively explore RNA-seq data through an integrated graphical and chat interface. Our method demonstrates a new way of working with transcriptome data, leveraging the power of natural language for single-cell data analysis and establishing an important building block for future AI-based bioinformatics research assistants.

bioinformatics↗

bioRxiv2023

Characterization of predictive power of extracellular signal recordings in a cerebral ischemia animal model

IntroductionGlobal cerebral ischemia leads to substantial and irreversible damage of brain tissue. As it progresses in a less severe course, certain strategies should be implemented to screen this condition on its early onset. The research aimed to characterize the local field potential (LFP) alterations recorded during the subacute phase of the cerebral ischemia animal model and provide their predictive power. MethodsThe extracellular signal recordings from the parietal cortex of animals were registered with a neural probe. The signal was amplified, filtered, digitized, and acquired with Intan amplifier and USB interface boards. The recordings were obtained both in normal conditions and after implementation of unilateral common carotid artery occlusion. The data analysis and classification were performed using NI Diadem software and custom-written code in IPython environment. The respective morphological changes were screened in cerebral cortex and hippocampus. The whole-brain slicing and TTC staining were used for infarct size evaluation. ResultsIn Fourier spectrograms of intact brain recordings, a peak at 14.4-15 Hz frequencies was detected, whereas this phenomenon was absent in cerebral ischemia model recordings. In channels cross-correlograms for intact and ischemic brain recordings, there was a clear difference detected in the maximum peak power. With autocorrelation analysis, the long lag rhythmicity was detected in normal brain recordings, while no rhythmicity was observed in ischemic brains. The morphological and behavioral analyses did not result in any significant changes and neural loss. The TTC staining failed to show any damaged area ipsilateral to the occluded common carotid artery. ConclusionWe have analyzed and described the major characteristics of the electrical activity that vary between neural populations of the parietal cortex of normal and ischemic brains. This data proves that LFP recordings can be used for further investigation of changes occurring in the subacute phase after unilateral common carotid artery occlusion.

neuroscience↗

bioRxiv2020

AN ADMIXTURE SIGNAL IN ARMENIANS AROUND THE END OF THE BRONZE AGE REVEALS WIDESPREAD POPULATION MOVEMENT ACROSS THE MIDDLE EAST

The Armenians, a population inhabiting the region in West Asia known as the Armenian Highland, has been argued to show a remarkable degree of population continuity since the Early Neolithic. Here we test the degree of continuity of this population as well as its plausible origin, by collating modern and ancient genomic data, and adding a number of novel contemporary genomes. We show that Armenians have indeed remained unadmixed through the Neolithic and at least until the first part of the Bronze Age, and fail to find any support for historical suggestions by Herodotus of an input from the Balkans. However, we do detect a genetic input of Sardinian-like ancestry during or just after the Middle-Late Bronze Age. A similar input at approximately the same time was detected in East Africa, suggesting large-scale movement both North and South of the Middle East. Whether such large-scale population movement was a result of climatic or cultural changes is unclear, as well as the true source of gene flow remains an open question that needs to be addressed in future ancient DNA studies.

genomics↗