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23 results for “nanoCAGE”
Genome alignments for the project "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol" - Protocol optimization
<p>Genome alignments for data generated in the project "<em>Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol – Optimization of the protocol.</em>" Files names indicate unique identifiers of MOIRAI workflow runs, with the following structure: library name, dot, workflow ID (OP-WORKFLOW-CAGEscan-short-reads-v2.0.), dot, timestamp. The raw (FASTQ) data of each library is also deposited in Zenodo (<a href="https://doi.org/10.5281/zenodo.250156">10.5281/zenodo.250156</a>). Library names correspond to the following runs:</p> <ul> <li> NC33: 151007_M00528_0161_000000000-AEBDC</li> <li> NC37: 151204_M00528_0173_000000000-AEBEF</li> <li> NC38: 151211_M00528_0175_000000000-AE9PJ</li> <li> NC39: 160122_M00528_0185_000000000-AEB18</li> <li> NC42: 160302_M00528_0192_000000000-AELYK</li> </ul> <p>This data can be analysed using the "CAGEr" software package available from Bioconductor. The "multiplex_files.zip" file contains tables indicating which samples are biological replicates of each other or negative controls.</p>
Sequence data for the article "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol" - single cells dataset
<p>Sequence data (Illumina MiSeq runs) for the article "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol". dataset of 2300 single cells. File names indicate unique sequencing runs. In the manuscripts, the informations about cell lines are found in the Supplemental Table 1. </p>
Sequence data for the article "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol" - Protocol optimization
<p>Sequence data (Illumina MiSeq runs) for the article "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol". Optimization of the protocol. Files names indicate unique run identifiers. In the manuscript, the link between unique run identifiers, cells and purpose of the experiment is found in the Supplemental Table 1. </p>
Data for "A combined experimental and computational exploration of heteroleptic cis-Pd2L2L'2 nanocages through geometric complementarity"
<div>In the following subdirectories are the input and output of GFN2-xTB and DFT calculations for this publication:</div> <div> </div> <div>chemrxiv: <strong><em><a href="https://doi.org/10.26434/chemrxiv-2024-s0mmw">https://doi.org/10.26434/chemrxiv-2024-s0mmw</a></em></strong></div> <div> </div> <div>Published: <strong><em><a href="https://doi.org/10.1002/chem.202403336">https://doi.org/10.1002/chem.202403336</a></em></strong></div> <div> </div> <div>Code repository: <a href="https://github.com/andrewtarzia/simple_het_construction">github.com/andrewtarzia/simple_het_construction</a></div> <div>Zenodo code DOI: <a href="https://doi.org/10.5281/zenodo.13649229">10.5281/zenodo.13649229</a></div> <div> </div> <div>data directory:</div> <div> <ul> <li>a spreadsheet with all final energy values and exchange energy calculations</li> <li>CSD Survey data, NPd_survey_data_261119.csv, for Pd centres</li> </ul> </div> <div>Naming convention for file conversions:</div> <div> <ul> <li>l1: 1DBF</li> <li>l2: 1Ph</li> <li>l3: 1Th</li> <li>la: 2DBF</li> <li>lb: 2Py</li> <li>lc: 2Ph</li> <li>ld: 2Th</li> </ul> </div> <div>Structure naming convention: </div> <div> <ul> <li> <em><strong>mX</strong></em> indicates a homoleptic cage with <em><strong>X</strong></em> Pd atoms, <strong><em>cis</em></strong>/<strong><em>trans</em></strong> are the cis/trans heteroleptic cages, respectively</li> </ul> </div> <div> <p> </p> <p>structures/xtb directory:</p> </div> <div> <ul> <li>contains the structures from GFN2-xTB/ALPB(DMSO) optimisations of stk-generated structures </li> </ul> </div> <div> </div> <div>structures/opt_*METHOD*_SP_*METHOD*_06-02-2024 directories:</div> <div> <ul> <li>All DFT was run by Victor Posligua</li> <li>contains the input files (.com), output files (.log) and structure files (.xyz/.mol) of DFT optimisations and single point energy calculations with each method</li> <li>When the opt method and SP method are the same, the final structure is included in .mol and .xyz formats</li> <li>However, if opt method is different from the SP method, the final structure is not included because only a single-point energy calculation was run. </li> <li>For example, there are no .mol or .xyz files for 'opt_PBE0_SP_B3LYP_06-02-2024’ since the structure is already in 'opt_PBE0_SP_PBE0_06-02-2024’.</li> <li>you’ll find 8 different folders:<br> <ul> <li>opt_PBE0_SP_PBE0_06-02-2024</li> <li>opt_PBE0_SP_B3LYP_06-02-2024</li> <li>opt_PBE0_SP_B97D3_06-02-2024</li> <li>opt_PBE0_SP_HSE_06-02-2024</li> <li>opt_B3LYP_SP_B3LYP_06-02-2024</li> <li>opt_B97D3_SP_B97D3_06-02-2024</li> <li>opt_HSE_SP_HSE_06-02-2024</li> <li>opt_GFN2-xTB_SP_PBE0_06-02-2024</li> </ul> </li> </ul> </div>
Data for "Diastereoselective Self-Assembly of Low-Symmetry PdnL2n Nanocages through Coordination-Sphere Engineering"
<p>In the following subdirectories are the input and outputs of cage and face analysis for:</p> <p>Published DOI: 10.1002/anie.202315451</p> <p>Previously uploaded in <span>10.5281/zenodo.8432296 and </span><a href="https://github.com/andrewtarzia/citable_data" rel="noopener noreferrer"><span>https://github.com/andrewtarzia/citable_data</span></a></p> <p>Note that all scripts are self-contained. There is some duplicate code between them.</p> scripts: <ul> <li> build_cages.py: <ul> <li>Builds the Pd2L4 cage models.</li> <li>Some manual optimisation is assumed.</li> <li>Paths for xTB and GULP are set to my machine.</li> <li>All outputs are relative to working directory.</li> </ul> </li> <li> build_dwall_triangles.py: <ul> <li>Builds the Pd3L6 cage models.</li> <li>Some manual optimisation is assumed.</li> <li>Paths for xTB and GULP are set to my machine.</li> <li>All outputs are relative to working directory.</li> </ul> </li> </ul>
Quantitative comparison of fluorescent proteins using protein nanocages in live cells
Open the record for dataset details and reuse information.
Computational Screening of Transition Metal Complexes as Guests in the Ga4L6-12 Nanocage
<p>Optimized geometries, scripts, experimental data curated from the literature from complexes, and CSD filtering data for "Computational Screening of Putative Transition Metal Complexes as Guests in the Ga4L6-12 Nanocage." </p>
Transcriptome profiling of derived-hepatocyte progenitors from human iPSCs with nanoCAGE - part 1 - sequencing data (FASTQ files)
<p>This repository contains raw sequencing data (FASTQ files) produced from Illumina MiSeq run IDs "170630_M00528_0292_000000000-B9JY8" (aka "NC_LIMMS") and "180221_M00528_0334_000000000-B6PJM" (aka "NC_LIMMS2") . Sequencing libraries were prepared following the latest version of the nanoCAGE protocol (Poulain et al., Methods Mol Biol. 2017;1543:57-109. doi: 10.1007/978-1-4939-6716-2_4). They respectively contain a mix of 24 ("NC_LIMMS") and 18 ("NC_LIMMS2") samples tagged by specific barcode sequences at the 5'-ends (see tables below). The tagmentation step included in the protocol was performed using an equimolar mix of 12 Nextera XT N-series index primers (N701 to N712), therefore "NNNNNNNN" was indicated as index sequence on the Illumina Sample Sheet for the demultiplexing (see tables below). Libraries were sequenced paired-end on Illumina MiSeq system with the MiSeq Reagent Kit v3 (150 cycles: 58 cycles used for READ1, 8 cycles used for the Index, and 84 cycles used for READ2). Genomic alignments (BED files) of paired-end reads on human genome assemblies hg19 and hg38 using the MOIRAI pipeline (Hasegawa et al. BMC Bioinformatics 2014 May 16;15:144. doi: 10.1186/1471-2105-15-144) were deposited at Zenodo under the following Digital Object Identifier: 10.5281/zenodo.1017276.</p> <p> </p> <p><em><strong>"170630_M00528_0292_000000000-B9JY8" ("NC_LIMMS") :</strong></em></p> <p><strong>ID Sample_name Barcode_number Barcode_sequence Index_sequence</strong></p> <p>1 iPSC_control_rep1 4 ACAGAT NNNNNNNN</p> <p>2 iPSC_control_rep2 24 ATCGTG NNNNNNNN</p> <p>3 iPSC_control_rep3 31 CACGAT NNNNNNNN</p> <p>4 S3P1_OK_rep1 36 CACTGA NNNNNNNN</p> <p>5 S3P1_OK_rep2 46 CTGACG NNNNNNNN</p> <p>6 S3P1_OK_rep3 63 GAGTGA NNNNNNNN</p> <p>7 S4P1_OK_rep1 79 GTATAC NNNNNNNN</p> <p>8 S4P1_OK_rep2 92 TCGAGC NNNNNNNN</p> <p>9 S4P1_OK_rep3 9 ACATGA NNNNNNNN</p> <p>10 S4P2_OK_rep1 21 ATCATA NNNNNNNN</p> <p>11 S4P2_OK_rep2 33 CACGTG NNNNNNNN</p> <p>12 S4P2_OK_rep3 45 CGATGA NNNNNNNN</p> <p>13 S1P1_rep1 57 GAGATA NNNNNNNN</p> <p>14 S1P1_rep2 69 GCTCTC NNNNNNNN</p> <p>15 S1P1_rep3 81 GTATGA NNNNNNNN</p> <p>16 S3P1_FAILED_rep1 93 TCGATA NNNNNNNN</p> <p>17 S3P1_FAILED_rep2 11 AGTAGC NNNNNNNN</p> <p>18 S3P1_FAILED_rep3 23 ATCGCA NNNNNNNN</p> <p>19 S4P1_FAILED_rep1 35 CACTCT NNNNNNNN</p> <p>20 S4P1_FAILED_rep2 47 CTGAGC NNNNNNNN</p> <p>21 S4P1_FAILED_rep3 59 GAGCGT NNNNNNNN</p> <p>22 S4P2_FAILED_rep1 71 GCTGCA NNNNNNNN</p> <p>23 S4P2_FAILED_rep2 83 TATAGC NNNNNNNN</p> <p>24 S4P2_FAILED_rep3 95 TCGCGT NNNNNNNN</p> <p> </p> <p><em><strong>"180221_M00528_0334_000000000-B6PJM" ("NC_LIMMS2"):</strong></em></p> <p><strong>ID Sample_name Barcode_number Barcode_sequence Index_sequence</strong></p> <p>25 PETRI_rep1 04 ACAGAT NNNNNNNN</p> <p>26 PETRI_rep2 24 ATCGTG NNNNNNNN</p> <p>27 PETRI_rep3 31 CACGAT NNNNNNNN</p> <p>28 BIOCHIP_E_rep1 6 CACTGA NNNNNNNN</p> <p>29 BIOCHIP_M_rep1 46 CTGACG NNNNNNNN</p> <p>30 BIOCHIP_S_rep1 63 GAGTGA NNNNNNNN</p> <p>31 BIOCHIP_E_rep2 79 GTATAC NNNNNNNN</p> <p>32 BIOCHIP_M_rep2 92 TCGAGC NNNNNNNN</p> <p>33 BIOCHIP_S_rep2 09 ACATGA NNNNNNNN</p> <p>34 BIOCHIP_E_rep3 21 ATCATA NNNNNNNN</p> <p>35 BIOCHIP_M_rep3 33 CACGTG NNNNNNNN</p> <p>36 BIOCHIP_S_rep3 45 CGATGA NNNNNNNN</p> <p>37 HEPATOCYTES_rep1 57 GAGATA NNNNNNNN</p> <p>38 HEPATOCYTES_rep2 69 GCTCTC NNNNNNNN</p> <p>39 iPSC_control_rep1-2 81 GTATGA NNNNNNNN</p> <p>40 BIOCHIP_E_rep2-2 93 TCGATA NNNNNNNN</p> <p>41 BIOCHIP_M_rep1-2 11 AGTAGC NNNNNNNN</p> <p>42 BIOCHIP_S_rep2-2 23 ATCGCA NNNNNNNN</p>
Transcriptome profiling of derived-hepatocyte progenitors from human iPSCs with nanoCAGE - part1 - genomic alignments (hg19 + hg38)
<p>This repository contains genomic alignments (BED files) of paired-end nanoCAGE sequencing data (CAGEscan data) collected from Illumina MiSeq run IDs "170630_M00528_0292_000000000-B9JY8" (aka "NC_LIMMS") and "180221_M00528_0334_000000000-B6PJM" (aka "NC_LIMMS2"). FASTQ files were processed with the MOIRAI pipeline OP-WORKFLOW-CAGEscan-short-reads-v2.1 (Hasegawa et al. BMC Bioinformatics 2014 May 16;15:144. doi: 10.1186/1471-2105-15-144.). Filtered pairs of reads were aligned on the human genome assemblies hg19 and hg38. See tables below for a detailed description of the samples contained in each nanoCAGE library, including barcodes and index sequences used for the demultiplexing of sequencing reads. Corresponding raw sequencing data files (FASTQ files) were deposited at Zenodo under the following Digital Object Identifier: 10.5281/zenodo.1014009.</p> <p> </p> <p><em><strong>"170630_M00528_0292_000000000-B9JY8" ("NC_LIMMS") :</strong></em></p> <p><strong>ID Sample_name Barcode_number Barcode_sequence Index_sequence</strong></p> <p>1 iPSC_control_rep1 4 ACAGAT NNNNNNNN</p> <p>2 iPSC_control_rep2 24 ATCGTG NNNNNNNN</p> <p>3 iPSC_control_rep3 31 CACGAT NNNNNNNN</p> <p>4 S3P1_OK_rep1 36 CACTGA NNNNNNNN</p> <p>5 S3P1_OK_rep2 46 CTGACG NNNNNNNN</p> <p>6 S3P1_OK_rep3 63 GAGTGA NNNNNNNN</p> <p>7 S4P1_OK_rep1 79 GTATAC NNNNNNNN</p> <p>8 S4P1_OK_rep2 92 TCGAGC NNNNNNNN</p> <p>9 S4P1_OK_rep3 9 ACATGA NNNNNNNN</p> <p>10 S4P2_OK_rep1 21 ATCATA NNNNNNNN</p> <p>11 S4P2_OK_rep2 33 CACGTG NNNNNNNN</p> <p>12 S4P2_OK_rep3 45 CGATGA NNNNNNNN</p> <p>13 S1P1_rep1 57 GAGATA NNNNNNNN</p> <p>14 S1P1_rep2 69 GCTCTC NNNNNNNN</p> <p>15 S1P1_rep3 81 GTATGA NNNNNNNN</p> <p>16 S3P1_FAILED_rep1 93 TCGATA NNNNNNNN</p> <p>17 S3P1_FAILED_rep2 11 AGTAGC NNNNNNNN</p> <p>18 S3P1_FAILED_rep3 23 ATCGCA NNNNNNNN</p> <p>19 S4P1_FAILED_rep1 35 CACTCT NNNNNNNN</p> <p>20 S4P1_FAILED_rep2 47 CTGAGC NNNNNNNN</p> <p>21 S4P1_FAILED_rep3 59 GAGCGT NNNNNNNN</p> <p>22 S4P2_FAILED_rep1 71 GCTGCA NNNNNNNN</p> <p>23 S4P2_FAILED_rep2 83 TATAGC NNNNNNNN</p> <p>24 S4P2_FAILED_rep3 95 TCGCGT NNNNNNNN</p> <p> </p> <p><em><strong>"180221_M00528_0334_000000000-B6PJM" ("NC_LIMMS2"):</strong></em></p> <p><strong>ID Sample_name Barcode_number Barcode_sequence Index_sequence</strong></p> <p>25 PETRI_rep1 04 ACAGAT NNNNNNNN</p> <p>26 PETRI_rep2 24 ATCGTG NNNNNNNN</p> <p>27 PETRI_rep3 31 CACGAT NNNNNNNN</p> <p>28 BIOCHIP_E_rep1 6 CACTGA NNNNNNNN</p> <p>29 BIOCHIP_M_rep1 46 CTGACG NNNNNNNN</p> <p>30 BIOCHIP_S_rep1 63 GAGTGA NNNNNNNN</p> <p>31 BIOCHIP_E_rep2 79 GTATAC NNNNNNNN</p> <p>32 BIOCHIP_M_rep2 92 TCGAGC NNNNNNNN</p> <p>33 BIOCHIP_S_rep2 09 ACATGA NNNNNNNN</p> <p>34 BIOCHIP_E_rep3 21 ATCATA NNNNNNNN</p> <p>35 BIOCHIP_M_rep3 33 CACGTG NNNNNNNN</p> <p>36 BIOCHIP_S_rep3 45 CGATGA NNNNNNNN</p> <p>37 HEPATOCYTES_rep1 57 GAGATA NNNNNNNN</p> <p>38 HEPATOCYTES_rep2 69 GCTCTC NNNNNNNN</p> <p>39 iPSC_control_rep1-2 81 GTATGA NNNNNNNN</p> <p>40 BIOCHIP_E_rep2-2 93 TCGATA NNNNNNNN</p> <p>41 BIOCHIP_M_rep1-2 11 AGTAGC NNNNNNNN</p> <p>42 BIOCHIP_S_rep2-2 23 ATCGCA NNNNNNNN</p> <p> </p>
Raw data for "Multimodal imaging of cubic Cu2O@Au nanocage formation via galvanic replacement using X-ray ptychography and nano diffraction"
<p><strong>Raw data for "Multimodal imaging of cubic Cu2O@Au nanocage formation via galvanic replacement using X-ray ptychography and nano diffraction"</strong></p> <p>The file "raw_data_ptychography_waxs.zip" contains one HDF5 archive for each scan. The archives are structured as follows:</p> <ul> <li>section experiment: <ul> <li>identifiers of the lightsource, beamline, beamtime, session number, and scan number</li> </ul> </li> <li>section measured: <ul> <li>N diffraction patterns of size 512x512 px used for ptychography</li> <li>N WAXS patterns of size 514x1030 px</li> <li>N scan positions in mm</li> <li>one detector mask of size 512x512 px used for ptychography</li> <li>one detector mask of size 514x1030 px used for WAXS</li> <li>slice separation in mm for multi slice reconstruction</li> </ul> </li> <li>section parameters: <ul> <li>distance between sample and forward detector (ptychography) in mm</li> <li>pixel size of forward detector (ptychography) in mm</li> <li>photon energy in keV</li> <li>cropping of diffraction patterns in px used for ptychographic reconstruction</li> </ul> </li> </ul> <p>The following lists show the scan numbers with their corresponding reaction times and slice separations for the in situ series recorded during growth of Cu<sub>2</sub>O nanocubes, as well as galvanic replacement with Au measured out of focus and in focus.</p> <p>Growth of Cu<sub>2</sub>O nanocubes:</p> <table> <tbody> <tr> <td><strong>scan number</strong></td> <td><strong>slice distance, mm</strong></td> <td><strong>reaction time, h</strong></td> </tr> <tr> <td>179</td> <td>1</td> <td>1.58</td> </tr> <tr> <td>185</td> <td>1</td> <td>3.59</td> </tr> <tr> <td>191</td> <td>1</td> <td>4.78</td> </tr> <tr> <td>192</td> <td>1</td> <td>5.21</td> </tr> <tr> <td>193</td> <td>1</td> <td>5.64</td> </tr> <tr> <td>194</td> <td>1</td> <td>6.08</td> </tr> <tr> <td>195</td> <td>1</td> <td>6.51</td> </tr> <tr> <td>196</td> <td>1</td> <td>6.94</td> </tr> <tr> <td>197</td> <td>1</td> <td>7.37</td> </tr> <tr> <td>198</td> <td>1</td> <td>7.81</td> </tr> <tr> <td>199</td> <td>1</td> <td>8.24</td> </tr> <tr> <td>200</td> <td>1</td> <td>8.67</td> </tr> <tr> <td>201</td> <td>1</td> <td>9.10</td> </tr> <tr> <td>202</td> <td>1</td> <td>9.53</td> </tr> <tr> <td>203</td> <td>1</td> <td>9.97</td> </tr> <tr> <td>204</td> <td>1</td> <td>10.41</td> </tr> <tr> <td>205</td> <td>1</td> <td>10.86</td> </tr> <tr> <td>207</td> <td>0.96</td> <td>11.53</td> </tr> <tr> <td>208</td> <td>0.94</td> <td>11.96</td> </tr> <tr> <td>209</td> <td>0.92</td> <td>12.41</td> </tr> <tr> <td>210</td> <td>0.9</td> <td>12.85</td> </tr> <tr> <td>211</td> <td>0.88</td> <td>13.29</td> </tr> <tr> <td>212</td> <td>0.86</td> <td>13.74</td> </tr> <tr> <td>213</td> <td>0.84</td> <td>14.19</td> </tr> <tr> <td>215</td> <td>0.8</td> <td>15.07</td> </tr> <tr> <td>216</td> <td>0.78</td> <td>15.50</td> </tr> <tr> <td>218</td> <td>0.74</td> <td>16.06</td> </tr> <tr> <td>219</td> <td>0.72</td> <td>16.50</td> </tr> <tr> <td>220</td> <td>0.7</td> <td>16.82</td> </tr> <tr> <td>221</td> <td>0.68</td> <td>17.08</td> </tr> <tr> <td>223</td> <td>0.64</td> <td>17.79</td> </tr> <tr> <td>225</td> <td>0.6</td> <td>18.53</td> </tr> </tbody> </table> <p>Galvanic replacement with Au measured out of focus:</p> <table> <tbody> <tr> <td><strong>scan number</strong></td> <td><strong>slice distance, mm</strong></td> <td><strong>reaction time, h</strong></td> </tr> <tr> <td>263</td> <td>1</td> <td>-0.53</td> </tr> <tr> <td>265</td> <td>1</td> <td>0.13</td> </tr> <tr> <td>266</td> <td>1</td> <td>0.38</td> </tr> <tr> <td>267</td> <td>1</td> <td>0.63</td> </tr> <tr> <td>268</td> <td>1</td> <td>0.89</td> </tr> <tr> <td>269</td> <td>1</td> <td>1.14</td> </tr> <tr> <td>270</td> <td>1</td> <td>1.40</td> </tr> <tr> <td>271</td> <td>1</td> <td>1.64</td> </tr> <tr> <td>272</td> <td>1</td> <td>1.90</td> </tr> <tr> <td>273</td> <td>1</td> <td>2.14</td> </tr> <tr> <td>274</td> <td>1</td> <td>2.39</td> </tr> <tr> <td>275</td> <td>1</td> <td>2.63</td> </tr> <tr> <td>276</td> <td>1</td> <td>2.87</td> </tr> <tr> <td>277</td> <td>1</td> <td>3.11</td> </tr> <tr> <td>278</td> <td>1</td> <td>3.35</td> </tr> <tr> <td>279</td> <td>1</td> <td>3.60</td> </tr> <tr> <td>280</td> <td>1</td> <td>3.84</td> </tr> <tr> <td>281</td> <td>1</td> <td>4.08</td> </tr> <tr> <td>282</td> <td>1</td> <td>4.32</td> </tr> <tr> <td>283</td> <td>1</td> <td>4.74</td> </tr> <tr> <td>284</td> <td>1</td> <td>5.15</td> </tr> <tr> <td>286</td> <td>1</td> <td>5.59</td> </tr> <tr> <td>287</td> <td>1</td> <td>6.01</td> </tr> <tr> <td>288</td> <td>1</td> <td>6.35</td> </tr> <tr> <td>289</td> <td>1</td> <td>6.74</td> </tr> <tr> <td>290</td> <td>1</td> <td>7.15</td> </tr> <tr> <td>291</td> <td>1</td> <td>7.55</td> </tr> <tr> <td>292</td> <td>1</td> <td>7.94</td> </tr> <tr> <td>293</td> <td>1</td> <td>8.35</td> </tr> <tr> <td>294</td> <td>1</td> <td>8.75</td> </tr> <tr> <td>295</td> <td>1</td> <td>9.16</td> </tr> <tr> <td>296</td> <td>1</td> <td>9.56</td> </tr> <tr> <td>297</td> <td>1</td> <td>9.96</td> </tr> </tbody> </table> <p>Galvanic replacement with Au measured in focus:</p> <table> <tbody> <tr> <td><strong>scan number</strong></td> <td><strong>slice distance, mm</strong></td> <td><strong>reaction time, h</strong></td> </tr> <tr> <td>117</td> <td>1</td> <td>0.33</td> </tr> <tr> <td>118</td> <td>1</td> <td>0.93</td> </tr> <tr> <td>119</td> <td>1</td> <td>1.51</td> </tr> <tr> <td>120</td> <td>1</td> <td>2.08</td> </tr> <tr> <td>121</td> <td>1</td> <td>2.66</td> </tr> <tr> <td>122</td> <td>1</td> <td>3.24</td> </tr> <tr> <td>123</td> <td>1</td> <td>3.87</td> </tr> <tr> <td>124</td> <td>1</td> <td>4.44</td> </tr> <tr> <td>125</td> <td>1</td> <td>5.02</td> </tr> <tr> <td>126</td> <td>1</td> <td>5.61</td> </tr> <tr> <td>127</td> <td>1</td> <td>6.19</td> </tr> <tr> <td>128</td> <td>1</td> <td>6.77</td> </tr> <tr> <td>129</td> <td>1</td> <td>7.35</td> </tr> <tr> <td>130</td> <td>1</td> <td>7.93</td> </tr> <tr> <td>131</td> <td>1</td> <td>8.50</td> </tr> </tbody> </table> <p>The files "waxs_detector_calibration_cu2o_growth.poni" and "waxs_detector_calibration_au_galvanic_replacement.poni" contain the PONI data to be used for azimuthal integration of WAXS patterns using the pyFAI library.</p> <p><strong>Ptychographic reconstructions</strong></p> <p>The file "ptychographic_reconstructions.zip" contains the ptychographic reconstructions shown in the article and supplementary information in tiff format.</p> <p>Stacks of images corresponding to time series:</p> <ul> <li>Figure 1b, 2: P06_Cu2O_growth_scans_00179-00225_entrance_window.tif</li> <li>Figure 1b, 2: P06_Cu2O_growth_scans_00179-00225_exit_window.tif</li> <li>Figure 1d, 4, 5: P06_Au_galvanic_replacement_de-focus_scans_00263-00297_exit_window.tif</li> <li>Figure 5c: P06_Au_galvanic_replacement_in-focus_scans_00117-00131_exit_window.tif</li> </ul> <p><strong>SEM and EDX</strong></p> <p>The file "SEM_EDX.zip" contains the SEM images and EDX maps shown in Figure 3 in png format. Subfolders indicate the reaction time.</p>
Targeting kidney proximal tubules by protein nanocages via glomerular filtration
GEO Series GSE131922. Mus musculus. 14 samples. Type: Expression profiling by high throughput sequencing.
NanoCAGE in ERα knockdown BM67 cells
GEO Series GSE120916. Mus musculus. 3 samples. Type: Expression profiling by high throughput sequencing; Other.
nanoCAGE reveals 5’ UTR features that define specific modes of translation of functionally related mTOR-sensitive mRNAs
GEO Series GSE77033. Homo sapiens. 1 samples. Type: Expression profiling by high throughput sequencing.
Epigenetic evolution of the Ly49 gene family [nanoCAGE]
GEO Series GSE226501. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
Expression profile (nanoCAGE-seq), chromatin accessibility (ATAC-seq) profile, and histone modification profile (ChIP-seq for H3K4me3, H3K9me3, and H3K27me3) during the course of mouse gonocyte develo
GEO Series GSE121118. Mus musculus. 56 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing; Other.
Assembly of Genetically Engineered Ionizable Protein Nanocage-based Nanozymes for Intracellular Superoxide Scavenging
GEO Series GSE282015. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome profiling of derived-hepatocyte progenitors from human iPSCs with nanoCAGE
GEO Series GSE136841. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing; Other.
Epigenetic coordination of transcriptional and translational programs in hypoxia. [nanocage]
GEO Series GSE243417. Homo sapiens. 27 samples. Type: Other.
Transcriptome profiling of derived-hepatocyte progenitors from human iPSCs with nanoCAGE - part2 - genomic alignments (hg19 + hg38)
<p>This repository contains genomic alignments (BED files) of paired-end nanoCAGE sequencing data (CAGEscan data) collected from Illumina MiSeq run IDs "181114_M00528_0390_000000000-C7P58" (aka "NC_LIMMS3") and "190218_M00528_0406_000000000-CB4HR" (aka "NC_LIMMS4") FASTQ files were processed with the MOIRAI pipeline OP-WORKFLOW-CAGEscan-short-reads-v2.1 (Hasegawa et al. BMC Bioinformatics 2014 May 16;15:144. doi: 10.1186/1471-2105-15-144.). Filtered pairs of reads were aligned on the human genome assemblies hg19 and hg38. See tables below for a detailed description of the samples contained in each nanoCAGE library, including barcodes and index sequences used for the demultiplexing of sequencing reads. Corresponding raw sequencing data files (FASTQ files) were deposited at Zenodo under the following Digital Object Identifier: 10.5281/zenodo.2572390.</p> <p><em><strong>"181114_M00528_0390_000000000-C7P58" ("NC_LIMMS3"):</strong></em></p> <p><strong>sample_name group barcode_sequence index_sequence</strong><br> LIMMS43_04_PETRI_S4D7_rep1 iPSC_CLONE_TODAI ACAGAT NNNNNNNN<br> LIMMS44_24_PETRI_S4D7_rep2 iPSC_CLONE_TODAI ATCGTG NNNNNNNN<br> LIMMS45_31_PETRI_S4D7_rep3 iPSC_CLONE_TODAI CACGAT NNNNNNNN<br> LIMMS46_36_PETRI_S4D14_rep1 iPSC_CLONE_TODAI CACTGA NNNNNNNN<br> LIMMS47_46_PETRI_S4D14_rep2 iPSC_CLONE_TODAI CTGACG NNNNNNNN<br> LIMMS48_63_PETRI_S4D14_rep3 iPSC_CLONE_TODAI GAGTGA NNNNNNNN<br> LIMMS49_79_PETRI_CELLARTIS_rep1 iPSC_CLONE_TODAI GTATAC NNNNNNNN<br> LIMMS50_92_PETRI_CELLARTIS_rep2 iPSC_CLONE_TODAI TCGAGC NNNNNNNN<br> LIMMS51_09_PETRI_CELLARTIS_rep3 iPSC_CLONE_TODAI ACATGA NNNNNNNN<br> LIMMS52_21_PETRI_TODAI_rep1 iPSC_CLONE_CELLARTIS ATCATA NNNNNNNN<br> LIMMS53_33_PETRI_TODAI_rep2 iPSC_CLONE_CELLARTIS CACGTG NNNNNNNN<br> LIMMS54_45_PETRI_TODAI_rep3 iPSC_CLONE_CELLARTIS CGATGA NNNNNNNN<br> LIMMS55_57_iPSC_rep1 CONTROL_iPSC GAGATA NNNNNNNN</p> <p><em><strong>"190218_M00528_0406_000000000-CB4HR" ("NC_LIMMS4"):</strong></em></p> <p><strong>sample_name group barcode_sequence index_sequence</strong><br> LIMMS56_04_iPSC_rep4 CONTROL_iPSC ACAGAT NNNNNNNN<br> LIMMS57_24_LSECS_1_11 LSECS_PETRI_MONO ATCGTG NNNNNNNN<br> LIMMS58_31_LSECS_2_11 LSECS_PETRI_MONO CACGAT NNNNNNNN<br> LIMMS59_36_LSECS_3_11 LSECS_PETRI_MONO CACTGA NNNNNNNN<br> LIMMS60_46_LSECS_1-06 LSECS_PETRI_MONO CTGACG NNNNNNNN<br> LIMMS61_63_B3_MONO_11_D3 BC_MONO_D3 GAGTGA NNNNNNNN<br> LIMMS62_79_B9_CO_10_D14 BC_CO_D14 GTATAC NNNNNNNN<br> LIMMS63_92_B13_CO_11_D3 BC_CO_D3 TCGAGC NNNNNNNN<br> LIMMS64_09_P2_10_D14 PETRI_MONO ACATGA NNNNNNNN<br> LIMMS65_21_P3_10_D14 PETRI_MONO ATCATA NNNNNNNN<br> LIMMS66_33_P3_11_D14 PETRI_MONO CACGTG NNNNNNNN<br> LIMMS67_45_B1_MONO_10_D14 BC_MONO_D14 CGATGA NNNNNNNN<br> LIMMS68_57_B2_MONO_10_D14 BC_MONO_D14 GAGATA NNNNNNNN<br> LIMMS69_69_B1_MONO_11_D14 BC_MONO_D14 GCTCTC NNNNNNNN<br> LIMMS70_81_B2_MONO_11_D14 BC_MONO_D14 GTATGA NNNNNNNN<br> LIMMS71_93_B6_CO_10_D14 BC_CO_D14 TCGATA NNNNNNNN<br> LIMMS72_11_B7_CO_10_D14 BC_CO_D14 AGTAGC NNNNNNNN<br> LIMMS73_23_B8_CO_10_D14 BC_CO_D14 ATCGCA NNNNNNNN<br> LIMMS74_35_B9_CO_11_D3 BC_CO_D3 CACTCT NNNNNNNN<br> LIMMS75_47_B11_CO_11_D14 BC_CO_D14 CTGAGC NNNNNNNN<br> LIMMS76_59_B12_CO_11_D14 BC_CO_D14 GAGCGT NNNNNNNN<br> LIMMS77_71_B14_CO_11_D14 BC_CO_D14 GCTGCA NNNNNNNN<br> LIMMS78_83_B15_CO_11_D14 BC_CO_D14 TATAGC NNNNNNNN<br> LIMMS79_95_iPSC_rep1_4 CONTROL_iPSC TCGCGT NNNNNNNN</p>
Transcriptome profiling of derived-hepatocyte progenitors from human iPSCs with nanoCAGE - part2 - sequencing data (FASTQ files)
<p>This repository contains raw sequencing data (FASTQ files) produced from Illumina MiSeq run IDs "181114_M00528_0390_000000000-C7P58" (aka "NC_LIMMS3") and "190218_M00528_0406_000000000-CB4HR" (aka "NC_LIMMS4") . Sequencing libraries were prepared following the latest version of the nanoCAGE protocol (Poulain et al., Methods Mol Biol. 2017;1543:57-109. doi: 10.1007/978-1-4939-6716-2_4). They respectively contain a mix of 13 ("NC_LIMMS3") and 24 ("NC_LIMMS4") samples tagged by specific barcode sequences at the 5'-ends (see tables below). The tagmentation step included in the protocol was performed using an equimolar mix of 12 Nextera XT N-series index primers (N701 to N712), therefore "NNNNNNNN" was indicated as index sequence on the Illumina Sample Sheet for the demultiplexing (see tables below). Libraries were sequenced paired-end on Illumina MiSeq system with the MiSeq Reagent Kit v3 (150 cycles: 58 cycles used for READ1, 8 cycles used for the Index, and 84 cycles used for READ2). Genomic alignments (BED files) of paired-end reads on human genome assemblies hg19 and hg38 using the MOIRAI pipeline (Hasegawa et al. BMC Bioinformatics 2014 May 16;15:144. doi: 10.1186/1471-2105-15-144) were deposited at Zenodo under the following Digital Object Identifier: 10.5281/zenodo.2572394.</p> <p><em><strong>"181114_M00528_0390_000000000-C7P58" ("NC_LIMMS3"):</strong></em></p> <p><strong>sample_name group barcode_sequence index_sequence</strong><br> LIMMS43_04_PETRI_S4D7_rep1 iPSC_CLONE_TODAI ACAGAT NNNNNNNN<br> LIMMS44_24_PETRI_S4D7_rep2 iPSC_CLONE_TODAI ATCGTG NNNNNNNN<br> LIMMS45_31_PETRI_S4D7_rep3 iPSC_CLONE_TODAI CACGAT NNNNNNNN<br> LIMMS46_36_PETRI_S4D14_rep1 iPSC_CLONE_TODAI CACTGA NNNNNNNN<br> LIMMS47_46_PETRI_S4D14_rep2 iPSC_CLONE_TODAI CTGACG NNNNNNNN<br> LIMMS48_63_PETRI_S4D14_rep3 iPSC_CLONE_TODAI GAGTGA NNNNNNNN<br> LIMMS49_79_PETRI_CELLARTIS_rep1 iPSC_CLONE_TODAI GTATAC NNNNNNNN<br> LIMMS50_92_PETRI_CELLARTIS_rep2 iPSC_CLONE_TODAI TCGAGC NNNNNNNN<br> LIMMS51_09_PETRI_CELLARTIS_rep3 iPSC_CLONE_TODAI ACATGA NNNNNNNN<br> LIMMS52_21_PETRI_TODAI_rep1 iPSC_CLONE_CELLARTIS ATCATA NNNNNNNN<br> LIMMS53_33_PETRI_TODAI_rep2 iPSC_CLONE_CELLARTIS CACGTG NNNNNNNN<br> LIMMS54_45_PETRI_TODAI_rep3 iPSC_CLONE_CELLARTIS CGATGA NNNNNNNN<br> LIMMS55_57_iPSC_rep1 CONTROL_iPSC GAGATA NNNNNNNN</p> <p><em><strong>"190218_M00528_0406_000000000-CB4HR" ("NC_LIMMS4"):</strong></em></p> <p><strong>sample_name group barcode_sequence index_sequence</strong><br> LIMMS56_04_iPSC_rep4 CONTROL_iPSC ACAGAT NNNNNNNN<br> LIMMS57_24_LSECS_1_11 LSECS_PETRI_MONO ATCGTG NNNNNNNN<br> LIMMS58_31_LSECS_2_11 LSECS_PETRI_MONO CACGAT NNNNNNNN<br> LIMMS59_36_LSECS_3_11 LSECS_PETRI_MONO CACTGA NNNNNNNN<br> LIMMS60_46_LSECS_1-06 LSECS_PETRI_MONO CTGACG NNNNNNNN<br> LIMMS61_63_B3_MONO_11_D3 BC_MONO_D3 GAGTGA NNNNNNNN<br> LIMMS62_79_B9_CO_10_D14 BC_CO_D14 GTATAC NNNNNNNN<br> LIMMS63_92_B13_CO_11_D3 BC_CO_D3 TCGAGC NNNNNNNN<br> LIMMS64_09_P2_10_D14 PETRI_MONO ACATGA NNNNNNNN<br> LIMMS65_21_P3_10_D14 PETRI_MONO ATCATA NNNNNNNN<br> LIMMS66_33_P3_11_D14 PETRI_MONO CACGTG NNNNNNNN<br> LIMMS67_45_B1_MONO_10_D14 BC_MONO_D14 CGATGA NNNNNNNN<br> LIMMS68_57_B2_MONO_10_D14 BC_MONO_D14 GAGATA NNNNNNNN<br> LIMMS69_69_B1_MONO_11_D14 BC_MONO_D14 GCTCTC NNNNNNNN<br> LIMMS70_81_B2_MONO_11_D14 BC_MONO_D14 GTATGA NNNNNNNN<br> LIMMS71_93_B6_CO_10_D14 BC_CO_D14 TCGATA NNNNNNNN<br> LIMMS72_11_B7_CO_10_D14 BC_CO_D14 AGTAGC NNNNNNNN<br> LIMMS73_23_B8_CO_10_D14 BC_CO_D14 ATCGCA NNNNNNNN<br> LIMMS74_35_B9_CO_11_D3 BC_CO_D3 CACTCT NNNNNNNN<br> LIMMS75_47_B11_CO_11_D14 BC_CO_D14 CTGAGC NNNNNNNN<br> LIMMS76_59_B12_CO_11_D14 BC_CO_D14 GAGCGT NNNNNNNN<br> LIMMS77_71_B14_CO_11_D14 BC_CO_D14 GCTGCA NNNNNNNN<br> LIMMS78_83_B15_CO_11_D14 BC_CO_D14 TATAGC NNNNNNNN<br> LIMMS79_95_iPSC_rep1_4 CONTROL_iPSC TCGCGT NNNNNNNN</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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