cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25378/janelia.17783336.v1
title: Classifier-identified bicycle genes lists

description: List of bicycle genes identified by the gene structure-based linear logistic regression classifier in each of 16 species, associated with Figure 1 from "Gene structure-based homology search identifies highly divergent putative effector gene family", Stern and Han, BioRxiv https://doi.org/10.1101/2021.09.24.461719.<br>Please contact Clair Han at hanc@janelia.hhmi.org with any questions.<br><br> See related materials in collection at https://doi.org/10.25378/janelia.c.5778905.
DOI: 10.25378/janelia.17783336.v2
title: Classifier-identified bicycle genes lists

description: List of bicycle genes identified by the gene structure-based linear logistic regression classifier in each of 16 species, associated with Figure 1 from "Gene structure-based homology search identifies highly divergent putative effector gene family", Stern and Han, BioRxiv https://doi.org/10.1101/2021.09.24.461719.<br>Please contact Clair Han at hanc@janelia.hhmi.org with any questions.<br><br> See related materials in collection at https://doi.org/10.25378/janelia.c.5778905.
DOI: 10.25378/janelia.18225080
title: Neuropixels datasets supporting main results of "Motor cortical output for skilled forelimb movement is selectively distributed across intratelencephalic and corticopontine projection neuron classes"

description: These are the core electrophysiological datasets supporting the conclusions of the work in the manuscript titled: "Motor cortical output for skilled forelimb movement is selectively distributed across intratelencephalic and corticopontine projection neuron classes". Primary datasets are Neuropixels recordings with reconstructed anatomical depth per unit and optotagging of a subset of neurons either Tlx3+ intratelencephalic neurons ("IT_") or Sim1+ corticopontine PT neurons ("PT_").<br>Briefly, we used a Neuropixels probe to record from the entire depth of mouse motor cortex and underlying striatum during performance of a operant joystick task. Simultaneous joystick position data (x,y) and licking at a reward port are found within associated "BehavioralVariables" data files within the directory structure. The physiological traces for each unit are the output of spike times and various useful alignments following spike sorting using JRClust and in most cases confirmed via parallel sorting with KiloSort. An associated Matlab script is provided that is sufficient to recreate the plots used in the manuscript.<br><br> See related materials in the collection: https://doi.org/10.25378/janelia.c.5795939<br>
DOI: 10.25378/janelia.18227924
title: Imaging datasets supporting main results of "Motor cortical output for skilled forelimb movement is selectively distributed across intratelencephalic and corticopontine projection neuron classes"

description: These are the core imaging datasets supporting the conclusions of the work in the manuscript titled "Motor cortical output for skilled forelimb movement is selectively distributed across intratelencephalic and corticopontine projection neuron classes". Imaging was conducted with Gcamp6f introduced into either Tlx3+ intratelencephalic neurons or Sim1+ corticopontine PT neurons as described in the preprint (https://doi.org/10.1101/772517). <br>Briefly, we used a resonant scanner 2 photon microscope to perform imaging in a single plane from the proximal dendrite of layer 5 neurons in the mouse motor cortex during performance of a operant joystick task. Simultaneous joystick position data (x,y) and licking at a reward port are aligned and contained within each dataset. Task variables (trial start, reward delivery, etc) are also captured within the csv. The physiological traces for each ROI are 'inferred spikes' extracted from dF/F traces from hand drawn ROIs as described in the manuscript. An associated Matlab script is provided that is sufficient to recreate the plots used in the manuscript.<br><br>See related materials in the collection: https://doi.org/10.25378/janelia.c.5795939
DOI: 10.25378/janelia.18227924.v1
title: Imaging datasets supporting main results of "Motor cortical output for skilled forelimb movement is selectively distributed across intratelencephalic and corticopontine projection neuron classes"

description: These are the core imaging datasets supporting the conclusions of the work in the manuscript titled "Motor cortical output for skilled forelimb movement is selectively distributed across intratelencephalic and corticopontine projection neuron classes". Imaging was conducted with Gcamp6f introduced into either Tlx3+ intratelencephalic neurons or Sim1+ corticopontine PT neurons as described in the preprint (https://doi.org/10.1101/772517). <br>Briefly, we used a resonant scanner 2 photon microscope to perform imaging in a single plane from the proximal dendrite of layer 5 neurons in the mouse motor cortex during performance of a operant joystick task. Simultaneous joystick position data (x,y) and licking at a reward port are aligned and contained within each dataset. Task variables (trial start, reward delivery, etc) are also captured within the csv. The physiological traces for each ROI are 'inferred spikes' extracted from dF/F traces from hand drawn ROIs as described in the manuscript. An associated Matlab script is provided that is sufficient to recreate the plots used in the manuscript.<br><br>See related materials in the collection: https://doi.org/10.25378/janelia.c.5795939
DOI: 10.25378/janelia.19560991
title: Multi-sequence alignment files

description: Multisequence alignment files for sequence logos in manuscript "Gene structure-based homology search identifies highly divergent putative effector gene family", Stern and Han, BioRxiv https://doi.org/10.1101/2021.09.24.461719. <br> Please contact Clair Han at hanc@janelia.hhmi.org with any questions.<br> See related materials in collection at https://doi.org/10.25378/janelia.c.5778905. <br> Hcor Fig 2B: Hcor_gene_cluster1_v5.5.6.mafft_auto.trimal_30.fa Fig 2C: Hcor_gene_cluster2_v5.5.6.mafft_auto.trimal_50.fa <br> Fig 3B: Hcor_bicycle_gene_100_v5.5.6ii.mafft_auto.fa Fig 3C: Hcor_bicycle_gene_200_v5.5.6ii.mafft_auto.fa Fig 3D: Hcor_bicycle_gene_300_v5.5.6ii.mafft_auto.fa Fig 3E: Hcor_bicycle_gene_400_v5.5.6ii.mafft_auto.fa <br> Tnig Fig 4B: Tnig_gene_cluster1_v5.5.6.mafft_auto.fa Fig 4C: Tnig_gene_cluster2_v5.5.6.mafft_auto.fa Fig 4D: Tnig_gene_cluster3_v5.5.6.mafft_auto.fa Fig 4E: Tnig_gene_cluster4_v5.5.6.mafft_auto.fa <br> Apis Fig 5A: Apis_bicycle_gene_100_200_v5.5.6.Mathers.mafft_auto.fa <br> Mper Fig S9C: Mper.bicycle_gene_200_v5.5.6.mafft_auto.fa <br> Pnig Fig S9D: Pnig.bicycle_gene_100_v5.5.6.mafft_auto.fa <br> Rmai Fig S9E: Rmai.bicycle_gene_200_v5.5.6.mafft_auto.fa <br> Cced Fig S9F: Cced.bicycle_gene_200_v5.5.6.mafft_auto.fa <br> Dvit Fig S10A: Dvit.bicycle_gene_v5.5.6.mafft_auto.fa <br> Mhir Fig S10B: Mhir.bicycle_gene_v5.5.6.mafft_auto.fa <br> Psol Fig S10C: Psol.gene_v5.5.6.mafft_auto.fa <br> <br>
DOI: 10.25378/janelia.19560991.v1
title: Multi-sequence alignment files

description: Multisequence alignment files for sequence logos in manuscript "Gene structure-based homology search identifies highly divergent putative effector gene family", Stern and Han, BioRxiv https://doi.org/10.1101/2021.09.24.461719. <br> Please contact Clair Han at hanc@janelia.hhmi.org with any questions.<br> See related materials in collection at https://doi.org/10.25378/janelia.c.5778905. <br> Hcor Fig 2B: Hcor_gene_cluster1_v5.5.6.mafft_auto.trimal_30.fa Fig 2C: Hcor_gene_cluster2_v5.5.6.mafft_auto.trimal_50.fa <br> Fig 3B: Hcor_bicycle_gene_100_v5.5.6ii.mafft_auto.fa Fig 3C: Hcor_bicycle_gene_200_v5.5.6ii.mafft_auto.fa Fig 3D: Hcor_bicycle_gene_300_v5.5.6ii.mafft_auto.fa Fig 3E: Hcor_bicycle_gene_400_v5.5.6ii.mafft_auto.fa <br> Tnig Fig 4B: Tnig_gene_cluster1_v5.5.6.mafft_auto.fa Fig 4C: Tnig_gene_cluster2_v5.5.6.mafft_auto.fa Fig 4D: Tnig_gene_cluster3_v5.5.6.mafft_auto.fa Fig 4E: Tnig_gene_cluster4_v5.5.6.mafft_auto.fa <br> Apis Fig 5A: Apis_bicycle_gene_100_200_v5.5.6.Mathers.mafft_auto.fa <br> Mper Fig S9C: Mper.bicycle_gene_200_v5.5.6.mafft_auto.fa <br> Pnig Fig S9D: Pnig.bicycle_gene_100_v5.5.6.mafft_auto.fa <br> Rmai Fig S9E: Rmai.bicycle_gene_200_v5.5.6.mafft_auto.fa <br> Cced Fig S9F: Cced.bicycle_gene_200_v5.5.6.mafft_auto.fa <br> Dvit Fig S10A: Dvit.bicycle_gene_v5.5.6.mafft_auto.fa <br> Mhir Fig S10B: Mhir.bicycle_gene_v5.5.6.mafft_auto.fa <br> Psol Fig S10C: Psol.gene_v5.5.6.mafft_auto.fa <br> <br>
DOI: 10.25378/janelia.19709311
title: Optimization of genetically encoded GABA indicator

description: The GENIE Project Team at HHMI Janelia has developed a second-generation genetically encoded GABA indicator, in collaboration with Jonathan Marvin and Loren Looger. The sensor is based on iGABASnFR (1), and has the following features, tested extensively in cultured neurons: <br> Positive-going version (iGABASnFR2) and negative-going version (iGABASnFR2n) iGABASnFR2: 4x higher sensitivity to APs than iGABASnFR, iGABASnFR2n: 2x higher sensitivity to APs than iGABASnFR. Both enable single-AP high-speed imaging Enables detection of signal in individual dendrites and synaptic boutons Higher affinity for GABA (iGABASnFR2: EC50: 6.4±0.2 μM, ~7x tighter than iGABASnFR, ΔF/Fmax=0.5±0.05, ~2x higher than iGABASnFR) Imaged with standard GFP filter set
DOI: 10.25378/janelia.19709311.v1
title: Optimization of genetically encoded GABA indicator

description: The GENIE Project Team at HHMI Janelia has developed a second-generation genetically encoded GABA indicator (Fig. 1a), in collaboration with Jonathan Marvin and Loren Looger. The sensor is based on iGABASnFR (Marvin, J.S., Shimoda, Y., Magloire, V. et al. A genetically encoded fluorescent sensor for in vivo imaging of GABA. Nat Methods 16, 763–770 (2019). https://doi.org/10.1038/s41592-019-0471-2), and has the following features, tested extensively in cultured neurons.
DOI: 10.25378/janelia.19709311.v2
title: Optimization of genetically encoded GABA indicator

description: The GENIE Project Team at HHMI Janelia has developed a second-generation genetically encoded GABA indicator (Fig. 1a), in collaboration with Jonathan Marvin and Loren Looger. The sensor is based on iGABASnFR (Marvin, J.S., Shimoda, Y., Magloire, V. et al. A genetically encoded fluorescent sensor for in vivo imaging of GABA. Nat Methods 16, 763–770 (2019). https://doi.org/10.1038/s41592-019-0471-2), and has the following features, tested extensively in cultured neurons.
DOI: 10.25378/janelia.19709398
title: jASAP voltage indicator optimization

description: ASAPs (Accelerated Sensor of Action Potentials), developed by Michael Lin (https://doi.org/10.1038/nn.3709, https://doi.org/10.1016/j.cell.2019.11.004), represents a class of voltage indicators that’s sensitive (from spike detection to subthreshold membrane potential reporting), fast (submillisecond level for recently published ASAP2f variant) and two-photon compatible. GENIE project team has put effort in optimizing ASAP voltage indicator. With our high-throughput HEK cell screening platform we identified one top hit, T392V mutation based on ASAP3, dramatically improve the sensitivity (by ~60%) without compromising kinetics. ASAP (T392V) variants performance was further tested in mammalian neurons (field stimulation screening and voltage clamp assay) and mouse visual cortex <em>in vivo</em>.
DOI: 10.25378/janelia.19709398.v1
title: jASAP voltage indicator optimization

description: ASAPs (Accelerated Sensor of Action Potentials), developed by Michael Lin (https://doi.org/10.1038/nn.3709, https://doi.org/10.1016/j.cell.2019.11.004), represents a class of voltage indicators that’s sensitive (from spike detection to subthreshold membrane potential reporting), fast (submillisecond level for recently published ASAP2f variant) and two-photon compatible. GENIE project team has put effort in optimizing ASAP voltage indicator. With our high-throughput HEK cell screening platform we identified one top hit, T392V mutation based on ASAP3, dramatically improve the sensitivity (by ~60%) without compromising kinetics. ASAP (T392V) variants performance was further tested in mammalian neurons (field stimulation screening and voltage clamp assay) and mouse visual cortex <em>in vivo</em>.
DOI: 10.25378/janelia.19709398.v2
title: jASAP voltage indicator optimization

description: ASAPs (Accelerated Sensor of Action Potentials), developed by Michael Lin (https://doi.org/10.1038/nn.3709, https://doi.org/10.1016/j.cell.2019.11.004), represents a class of voltage indicators that’s sensitive (from spike detection to subthreshold membrane potential reporting), fast (submillisecond level for recently published ASAP2f variant) and two-photon compatible. GENIE project team has put effort in optimizing ASAP voltage indicator. With our high-throughput HEK cell screening platform we identified one top hit, T392V mutation based on ASAP3, dramatically improve the sensitivity (by ~60%) without compromising kinetics. ASAP (T392V) variants performance was further tested in mammalian neurons (field stimulation screening and voltage clamp assay) and mouse visual cortex <em>in vivo</em>.
DOI: 10.25378/janelia.20133356
title: jrc_mus-liver Ariadne.ai organelle segmentations

description: Organelle segmentations generated using Ariadne.ai, an automatic segmentation service applied to a FIB-SEM mouse liver dataset subvolume. <br> This dataset captures a region within the mouse liver that includes several structures of metabolic significance. The data set contains profiles of many complete hepatocytes and their surrounding sinusoids and bile ductules. Some hepatocytes show two nuclei due to their enormous metabolic activity. Perforated endothelial cells and Kupffer cells form the lining of sinusoids. Inside each hepatocyte, many metabolic relevant organelles such as ER, mitochondria, lipid droplets and their structural relationship can be visualized in their entirety. <br> Sample: Wild-type, 8 week old mouse, strain: C57BL/6 from Jackson Lab Dataset ID: jrc_mus-liver EM Data DOI: 10.25378/janelia.16913047 EM voxel size (nm): 8.0 x 8.0 x 8.0 (X, Y, Z) Segmentation voxel size (nm): 8.0 x 8.0 x 8.0 (X, Y, Z) Segmentation offset (nm): 30984, 30912, 15728 (X, Y, Z) Dataset URL: https://data.janelia.org/lDE1m Visualization Website: https://openorganelle.janelia.org/datasets/jrc_mus-liver Segmented Organelles: Plasma membrane, Endoplasmic Reticulum, Mitochondria, Mitochondria Cristae, Nucleus
DOI: 10.25378/janelia.20133356.v1
title: jrc_mus-liver Ariadne.ai organelle segmentations

description: Organelle segmentations generated using Ariadne.ai, an automatic segmentation service applied to a FIB-SEM mouse liver dataset subvolume. <br> This dataset captures a region within the mouse liver that includes several structures of metabolic significance. The data set contains profiles of many complete hepatocytes and their surrounding sinusoids and bile ductules. Some hepatocytes show two nuclei due to their enormous metabolic activity. Perforated endothelial cells and Kupffer cells form the lining of sinusoids. Inside each hepatocyte, many metabolic relevant organelles such as ER, mitochondria, lipid droplets and their structural relationship can be visualized in their entirety. <br> Sample: Wild-type, 8 week old mouse, strain: C57BL/6 from Jackson Lab Dataset ID: jrc_mus-liver EM Data DOI: 10.25378/janelia.16913047 EM voxel size (nm): 8.0 x 8.0 x 8.0 (X, Y, Z) Segmentation voxel size (nm): 8.0 x 8.0 x 8.0 (X, Y, Z) Segmentation offset (nm): 30984, 30912, 15728 (X, Y, Z) Dataset URL: https://data.janelia.org/lDE1m Visualization Website: https://openorganelle.janelia.org/datasets/jrc_mus-liver Segmented Organelles: Plasma membrane, Endoplasmic Reticulum, Mitochondria, Mitochondria Cristae, Nucleus
DOI: 10.25378/janelia.20137250
title: jrc_mus-liver organelle predictions

description: A collection of ground truth data, raw predictions, and refined predictions performed on a mouse liver FIB-SEM dataset. This dataset captures a region within the mouse liver that includes several structures of metabolic significance. The data set contains profiles of many complete hepatocytes and their surrounding sinusoids and bile ductules. Some hepatocytes show two nuclei due to their enormous metabolic activity. Perforated endothelial cells and Kupffer cells form the lining of sinusoids. Inside each hepatocyte, many metabolic relevant organelles such as ER, mitochondria, lipid droplets and their structural relationship can be visualized in their entirety. Sample: Wild-type, 8 week old mouse, strain: C57BL/6 from Jackson Lab Dataset ID: jrc_mus-liver EM Data DOI: 10.25378/janelia.16913047 EM voxel size (nm): 8.0 x 8.0 x 8.0 (X, Y, Z) Segmentation voxel size (nm): 8.0 x 8.0 x 8.0 (X, Y, Z) Dataset URL: https://data.janelia.org/dyugw Visualization Website: https://openorganelle.janelia.org/datasets/jrc_mus-liver Segmented Organelles: ER, ER mem, Nucleus, PM, Mito, Mito mem, ECS Included in Dataset: predictions, segmentations, ground truth
DOI: 10.25378/janelia.20137250.v1
title: jrc_mus-liver organelle predictions

description: A collection of ground truth data, raw predictions, and refined predictions performed on a mouse liver FIB-SEM dataset. This dataset captures a region within the mouse liver that includes several structures of metabolic significance. The data set contains profiles of many complete hepatocytes and their surrounding sinusoids and bile ductules. Some hepatocytes show two nuclei due to their enormous metabolic activity. Perforated endothelial cells and Kupffer cells form the lining of sinusoids. Inside each hepatocyte, many metabolic relevant organelles such as ER, mitochondria, lipid droplets and their structural relationship can be visualized in their entirety. Sample: Wild-type, 8 week old mouse, strain: C57BL/6 from Jackson Lab Dataset ID: jrc_mus-liver EM Data DOI: 10.25378/janelia.16913047 EM voxel size (nm): 8.0 x 8.0 x 8.0 (X, Y, Z) Segmentation voxel size (nm): 8.0 x 8.0 x 8.0 (X, Y, Z) Dataset URL: https://data.janelia.org/dyugw Visualization Website: https://openorganelle.janelia.org/datasets/jrc_mus-liver Segmented Organelles: ER, ER mem, Nucleus, PM, Mito, Mito mem, ECS Included in Dataset: predictions, segmentations, ground truth
DOI: 10.7284/147020
title: GNSS (Global Navigation Satellite System) data collected during research cruise SP2127 using a Trimble ABX-Two instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/147015
title: Gyrocompass data collected during research cruise SP2127 using a Furuno Furuno SC-30 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/147014
title: Meteorological Station data collected during research cruise SP2127 using a SIO MET-System instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/147019
title: Singlebeam Echosounder data collected during research cruise SP2127 using a Knudsen 3260 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/147013
title: Winch data collected during research cruise SP2127 using a Markey DEYSH-3 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149925
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise SP2201 using a Hawaii UHDAS instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149929
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise SP2201 using a SeaBird SBE-911+ instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149930
title: GNSS (Global Navigation Satellite System) data collected during research cruise SP2201 using a Furuno GP-150 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149931
title: GNSS (Global Navigation Satellite System) data collected during research cruise SP2201 using a Furuno GP-170 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149932
title: GNSS (Global Navigation Satellite System) data collected during research cruise SP2201 using a Trimble ABX-Two instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149928
title: Gyrocompass data collected during research cruise SP2201 using a Furuno Furuno SC-30 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149927
title: Meteorological Station data collected during research cruise SP2201 using a SIO MET-System instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149926
title: Winch data collected during research cruise SP2201 using a Markey DEYSH-3 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149933
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise SP2202 using a Hawaii UHDAS instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149937
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise SP2202 using a SeaBird SBE-911+ instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149938
title: GNSS (Global Navigation Satellite System) data collected during research cruise SP2202 using a Furuno GP-150 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149939
title: GNSS (Global Navigation Satellite System) data collected during research cruise SP2202 using a Furuno GP-170 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149940
title: GNSS (Global Navigation Satellite System) data collected during research cruise SP2202 using a Trimble ABX-Two instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149936
title: Gyrocompass data collected during research cruise SP2202 using a Furuno Furuno SC-30 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149935
title: Meteorological Station data collected during research cruise SP2202 using a SIO MET-System instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149934
title: Winch data collected during research cruise SP2202 using a Markey DEYSH-3 instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149941
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise SP2203 using a Hawaii UHDAS instrument system onboard the platform RV Robert Gordon Sproul

description: Original (unprocessed) data collected during a Field_expedition