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CERN / The Human Cell ATLAS
_AI Art Body Data Painting for Sparks_Geneva
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STATEMENT
Ouchhh collaborated with CERN for Spark Forum_Future Technology for Health.
“Sparks! is part of the CERN & Society programme. CERN & Society activities are only possible thanks to support received from partners, in particular Rolex and its long-standing association with the organisation. The 2022 Sparks! event is also supported by the Didier et Martine Primat Foundation.
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STATEMENT
Ouchhh tried to create artistic self-portrait of humanity with AI and data.
Ouchhh collected data from The Human Cell Atlas. The Human Cell Atlas Project brings together an international community of biologists, clinicians, technologists, physicists, computational scientists, software engineers, and mathematicians. This community of scientists with diverse expertise share the common goal of creating a comprehensive reference map of all human cells as a basis for understanding human health and diagnosing, monitoring, and treating disease. Without maps of different cell types, where they are located in the body, and the genes they express, we cannot describe all cellular activities and understand the biological networks that direct them. Very recently, new tools, such as single-cell genomics, have for the first time put this goal within reach.”
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STATEMENT
The Human Cell Atlas Project is a project that aims to create a broad map of all human cells that cooperates with the studies of a lot of international scientists with wide expertise. In order for us to create artistic visualizations from the data collected from different studies, we used single-cell RNA-seq data from different tissues. RNA-seq is a novel technique for gathering more detailed information from the genome by quantitatively analyzing the RNA molecules in a sample. To make the analysis on the data we first preprocess and normalized the scRNA-seq data. After these processes, we had a dataset that belongs to a hundred-dimensionals universe. So, in order to visualize, and ultimately create a baseline for artistic expression, we deployed Auto Encoders and PCA analysis to make the data visible to the human eye. Auto Encoders is a machine learning technique that deals with representing higher dimensional data in lower dimensions. After reducing the dimension of the data to three dimensions we used tSNE algorithm to visualize hidden clusters in the data.
>SCIENTIFIC AI DATA PAINTING JOURNEY
The Human Cell Atlas Project is a project that aims to create a broad map of all human cells that cooperates with the studies of a lot of international scientists with wide expertise. In order for us to create artistic visualizations from the data collected from different studies, we used single-cell RNA-seq data from different tissues. RNA-seq is a novel technique for gathering more detailed information from the genome by quantitatively analyzing the RNA molecules in a sample. To make the analysis on the data we first preprocess and normalized the scRNA-seq data. After these processes, we had a dataset that belongs to a hundred-dimensionals universe.
So, in order to visualize, and ultimately create a baseline for artistic expression, we deployed Auto Encoders and PCA analysis to make the data visible to the human eye. Auto Encoders is a machine learning technique that deals with representing higher dimensional data in lower dimensions. After reducing the dimension of the data to three dimensions we used tSNE algorithm to visualize hidden clusters in the data.
