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New pipeline figures added in three notebooks
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tutorials/01-DataJoint Basics.ipynb

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"\n",
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"A [DataJoint pipeline](https://datajoint.com/docs/core/datajoint-python/0.14/concepts/terminology/) contains database table definitions, dependencies, and associated computations, together with the transformations underlying a DataJoint workflow. \n",
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"\n",
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"The following figure is an example of a DataJoint pipeline from [Optogenetics Element](https://datajoint.com/docs/elements/element-optogenetics/0.1/):\n",
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"The following figure is an example pipeline using [DataJoint Element for Multi-photon Calcium Imaging](https://datajoint.com/docs/elements/element-optogenetics/0.1/):\n",
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"\n",
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"![pipeline](https://raw.githubusercontent.com/datajoint/element-optogenetics/main/images/pipeline.svg)\n",
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"![pipeline](../images/pipeline-calcium-imaging.svg)\n",
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"\n",
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"A **well-designed data pipeline**: \n",
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"- 1. Collects, organizes, and stores **every relevant piece of information during the scientific research**\n",

tutorials/02-Calcium Imaging Imported Tables.ipynb

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"source": [
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"Welcome back! The practical example of this session is Calcium Imaging! \n",
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"\n",
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"![pipeline](../images/pipeline-calcium-imaging.svg)\n",
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"\n",
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"During this session you will learn:\n",
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"* To import neuron imaging data from data files into an `Imported` table\n",

tutorials/04-Electrophysiology Imported Tables.ipynb

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"cell_type": "markdown",
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"Welcome back! In this session, we are going to continue working with the pipeline for the mouse electrophysiology example. \n",
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"Welcome back! In this session, we are going to continue working with the pipeline for the mouse electrophysiology example.\n",
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"\n",
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"![pipeline](../images/pipeline-calcium-imaging.svg)\n",
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"\n",
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"In this session, we will learn to:\n",
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"\n",

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