cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34740/kaggle/dsv/5048509
title: The World's Billionaires Dataset 1987~2022
DOI: 10.5517/ccdc.csd.cc28qd1g
title: CCDC 2106885: Experimental Crystal Structure Determination

description: Related Article: Snehasish Thakur, Wahedur Sk, Rosa M. Gomila, Antonio Frontera, Shouvik Chattopadhyay|2023|Inorg.Chim.Acta|549|121411|doi:10.1016/j.ica.2023.121411
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.7564529
title: PolarBearVidID: A Video-based Re-Identification Benchmark Dataset for Polar Bears

description: <em><strong>The peer-reviewed publication for this dataset has now been published in Animals, an MDPI journal, and can be accessed here: https://doi.org/10.3390/ani13050801. Please cite this when using the dataset.</strong></em> <em>PolarBearVidID</em> includes 13 individual polar bears housed in six institutions. Each identity has 110 sequences on average. The maximum length of the sequences is 8 seconds, respectively 100 frames at a frame rate of 12.5 frames per second. The average length of the sequences is 96.69 images. In total, the dataset includes 1431 sequences. The resolution of the images is set to 256 x 128 pixels. Finally, <em>PolarBearVidID</em> is the first dataset to enable utilizing the movement of a non-human species as a feature for the task of re-identification.
DOI: 10.5281/zenodo.7564528
title: PolarBearVidID: A Video-based Re-Identification Benchmark Dataset for Polar Bears

description: <em><strong>The peer-reviewed publication for this dataset has now been published in Animals, an MDPI journal, and can be accessed here: https://doi.org/10.3390/ani13050801. Please cite this when using the dataset.</strong></em> <em>PolarBearVidID</em> includes 13 individual polar bears housed in six institutions. Each identity has 110 sequences on average. The maximum length of the sequences is 8 seconds, respectively 100 frames at a frame rate of 12.5 frames per second. The average length of the sequences is 96.69 images. In total, the dataset includes 1431 sequences. The resolution of the images is set to 256 x 128 pixels. Finally, <em>PolarBearVidID</em> is the first dataset to enable utilizing the movement of a non-human species as a feature for the task of re-identification.
DOI: 10.6084/m9.figshare.22106153.v5
title: LeakPair: An automated memory leak repair tool for Single Page Applications

description: LeakPair: An automated memory leak repair tool for Single Page Applications
DOI: 10.15151/esrf-es-1080756680
title: IBS BAG

description: The IBS BAG includes in this proposal IBS teams and external groups from iRTSV/CEA (Grenoble), CEA-Cadarache (St Paul lez Durance) and IRBA (Brétigny-sur-Orge). We study structure-function relationships of proteins emphasizing in human health, biotechnology and methodology. Most of the projects are a continuation of the MX-2329 proposal and can be grouped in different topics as follows: host-pathogen interaction, new drug targets, fundamental cellular mechanisms, membrane proteins, intrinsically disordered proteins, biotechnological applications and methodology. Some of these projects use integrative approaches (X-ray crystallography, SAXS, NMR (and cryo-EM), together with other biophysical studies) with the aim to fully understand the complexity of the biological macromolecular systems on study. Some teams are dedicated to serial crystallography and its developments, for which the ESRF-EBS has become the perfect tool.
DOI: 10.5281/zenodo.7669108
title: Dataset of veterinary books from Scopus website related to health and disease

description: the dataset was in CSV form
DOI: 10.5281/zenodo.7669107
title: Dataset of veterinary books from Scopus website related to health and disease

description: the dataset was in CSV form
DOI: 10.5281/zenodo.7669117
title: Tampere - Vuores daily temperature

description: Daily temperature records for 2020-2022 in Vuores neighbourhood in Tampere.
DOI: 10.5281/zenodo.7669118
title: Tampere - Vuores daily temperature

description: Daily temperature records for 2020-2022 in Vuores neighbourhood in Tampere.
DOI: 10.5519/qd.b0we0ftz
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (68544 records)
DOI: 10.5281/zenodo.7572544
title: PanGenie results generated for Minigraph-Cactus paper

description: <strong>PanGenie results generated for Minigraph-Cactus paper</strong> PanGenie (v2.1.0) was used to genotype a subset of 100 trios (300 samples) from the 1000 Genomes based on VCFs generated from the Minigraph-Cactus graphs for GRCh38 and CHM13, as well as the HGSVC VCF. This repository contains the resulting genotypes for SNPs, indels and SVs. See README.txt for details on the files.
DOI: 10.5281/zenodo.7572545
title: PanGenie results generated for Minigraph-Cactus paper

description: <strong>PanGenie results generated for Minigraph-Cactus paper</strong> PanGenie (v2.1.0) was used to genotype a subset of 100 trios (300 samples) from the 1000 Genomes based on VCFs generated from the Minigraph-Cactus graphs for GRCh38 and CHM13. This repository contains the resulting genotypes for SNPs, indels and SVs. See README.txt for details on the files.
DOI: 10.5281/zenodo.7611789
title: PanGenie results generated for Minigraph-Cactus paper

description: <strong>PanGenie results generated for Minigraph-Cactus paper</strong> PanGenie (v2.1.0) was used to genotype a subset of 100 trios (300 samples) from the 1000 Genomes based on VCFs generated from the Minigraph-Cactus graphs for GRCh38 and CHM13, as well as the HGSVC VCF. This repository contains the resulting genotypes for SNPs, indels and SVs. See README.txt for details on the files.
DOI: 10.5281/zenodo.7660118
title: PanGenie results generated for Minigraph-Cactus paper

description: <strong>PanGenie results generated for Minigraph-Cactus paper</strong> PanGenie (v2.1.0) was used to genotype a subset of 100 trios (300 samples) from the 1000 Genomes based on VCFs generated from the Minigraph-Cactus graphs for GRCh38 and CHM13, as well as the HGSVC VCF. This repository contains the resulting genotypes for SNPs, indels and SVs. See README.txt for details on the files.
DOI: 10.5281/zenodo.7669083
title: PanGenie results generated for Minigraph-Cactus paper

description: <strong>PanGenie results generated for Minigraph-Cactus paper</strong> PanGenie (v2.1.0) was used to genotype a subset of 100 trios (300 samples) from the 1000 Genomes based on VCFs generated from the Minigraph-Cactus graphs for GRCh38 and CHM13, as well as the HGSVC VCF. This repository contains the resulting genotypes for SNPs, indels and SVs. See README.txt for details on the files.
DOI: 10.5281/zenodo.7669145
title: Tampere - Urban green space accessibility and distribution

description: Results of the evaluation of urban green space accessibility and distribution in Vuores neighbourhood in Tampere.
DOI: 10.5281/zenodo.7669144
title: Tampere - Urban green space accessibility and distribution

description: Results of the evaluation of urban green space accessibility and distribution in Vuores neighbourhood in Tampere.
DOI: 10.5281/zenodo.7669159
title: Tampere - Biodiversity surveys and species diversity

description: Results of the biodiversity surveys and corresponding evaluation of the diversity of species in Tampere.
DOI: 10.5281/zenodo.7669158
title: Tampere - Biodiversity surveys and species diversity

description: Results of the biodiversity surveys and corresponding evaluation of the diversity of species in Tampere.
DOI: 10.25403/upresearchdata.22140605
title: Modelling linear spectra of plant light-harvesting complexes

description: This datasets consist of four Keras neural network (ANN) models and simulated linear spectra. Three of the models predict the pigment energies and other molecular parameters of the light-harvesting complex CP29 from linear spectra at 77 K and room temperature. The spectra required are the absorption, fluorescence, linear dichroism, and circular dichroism (CD) spectra. The ANNs take as input a joined vector of the spectra and they output the molecular parameters. One of the models predict all parameters from all of the spectra. Another uses all spectra apart from CD spectra to predict all of the parameters. The third model predicts only the energies (i.e., not the other molecular parameters) from all of the spectra. It should be clear from the filenames which is which. The fourth model predicts the linear spectra from the energies and molecular parameters. The spectral data sets contain absorption- and fluorescence-type linear spectra calculated for a dimer system with a system-bath interaction similar to that of plant light-harvesting complexes. A phonon continuum and eight chlorophyl high-frequency modes were included in the spectral density that characterises the system-bath interaction. Spectra were calculated for different site energy gaps (0 to 500 per cm) and couplings (-55 to 55 per cm) and also for different exciton energy gaps for strong couplings (&gt;300 per cm). To calculate the spectra, an exact stochastic path integral method was used, together with a number of approximate methods (the Full Cumulant Expansion, complex time-dependent Redfield (ctR), Redfield, modified Redfield, and a reorganisation-shifted version of the ctR method---the latter is applicable only for fluorescence spectra). The energy gaps, couplings, and dipole factors are indicated in the files.
DOI: 10.25403/upresearchdata.22140605.v1
title: Modelling linear spectra of plant light-harvesting complexes

description: This datasets consist of four Keras neural network (ANN) models and simulated linear spectra. Three of the models predict the pigment energies and other molecular parameters of the light-harvesting complex CP29 from linear spectra at 77 K and room temperature. The spectra required are the absorption, fluorescence, linear dichroism, and circular dichroism (CD) spectra. The ANNs take as input a joined vector of the spectra and they output the molecular parameters. One of the models predict all parameters from all of the spectra. Another uses all spectra apart from CD spectra to predict all of the parameters. The third model predicts only the energies (i.e., not the other molecular parameters) from all of the spectra. It should be clear from the filenames which is which. The fourth model predicts the linear spectra from the energies and molecular parameters. The spectral data sets contain absorption- and fluorescence-type linear spectra calculated for a dimer system with a system-bath interaction similar to that of plant light-harvesting complexes. A phonon continuum and eight chlorophyl high-frequency modes were included in the spectral density that characterises the system-bath interaction. Spectra were calculated for different site energy gaps (0 to 500 per cm) and couplings (-55 to 55 per cm) and also for different exciton energy gaps for strong couplings (&gt;300 per cm). To calculate the spectra, an exact stochastic path integral method was used, together with a number of approximate methods (the Full Cumulant Expansion, complex time-dependent Redfield (ctR), Redfield, modified Redfield, and a reorganisation-shifted version of the ctR method---the latter is applicable only for fluorescence spectra). The energy gaps, couplings, and dipole factors are indicated in the files.
DOI: 10.5281/zenodo.7669166
title: Tampere - Awareness of citizens regarding urban nature and ecosystem services

description: Results of the awareness of citizens regarding urban nature and ecosystem services survey among residents of Vuores neighbourhood in Tampere.
DOI: 10.5281/zenodo.7669167
title: Tampere - Awareness of citizens regarding urban nature and ecosystem services

description: Results of the awareness of citizens regarding urban nature and ecosystem services survey among residents of Vuores neighbourhood in Tampere.
DOI: 10.11588/data/veeidp/tqxc8q
title: BZ64_5_Block_7_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/z8gwp8
title: State_Global_SessionRate_4_7_3_0lag.mat

description: :unav
DOI: 10.11588/data/veeidp/rrcpdd
title: permutationPrecision.m

description: :unav
DOI: 10.11588/data/veeidp/fswrns
title: permutationTest.png

description: :unav
DOI: 10.11588/data/veeidp/hkp7ww
title: BZ64_8_Block_6_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/f3lmk3
title: BZ64_1_Block_7_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/7vcnnh
title: BlockTms.mat

description: :unav
DOI: 10.11588/data/veeidp/ongrql
title: BZ64_5_161006_11_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/rarq3q
title: FUNCTION_RATE_new.m

description: :unav
DOI: 10.11588/data/veeidp/b2jeyt
title: BZ64_6_160917_14_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/xhkeni
title: BZ64_4_161005_19_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/ae8lpj
title: Same_State_SessionRate.mat

description: :unav
DOI: 10.11588/data/veeidp/t6p1zq
title: BZ64_7_Block_7_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/nbvxtn
title: BZ64_7_160913_16_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/xoamhx
title: BZ64_6_160921_13_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/kjpz3n
title: BZ64_7_160921_17_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/qeih0y
title: BZ64_7_Block_4_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/ddkhie
title: PermutationTest LICENSE.txt

description: :unav
DOI: 10.11588/data/veeidp/1t5dw1
title: BZ64_6_160917_14_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/hkqdir
title: BZ64_1_161006_13_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/dppi4h
title: PermutationTest README.md

description: :unav
DOI: 10.11588/data/veeidp/jzzohe
title: BZ64_5_160913_16_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/edcdyl
title: ReadMe.txt

description: :unav
DOI: 10.11588/data/veeidp/9ebtfb
title: BZ64_7_160921_14_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/xfxzgw
title: BZ64_4_Block_7_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/fyipky
title: Same_State_Summary.mat

description: :unav
DOI: 10.11588/data/veeidp/1hmi1g
title: BZ64_6_160921_18_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/9kssbt
title: State_UnitSpkTimes_575_min.mat

description: :unav
DOI: 10.11588/data/veeidp/y3khjk
title: BZ64_6_160921_13_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/wjnfjr
title: BZ64_1_161006_13_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/6aba8j
title: Rate_Variant_Int_Global_Permutation_Units_473.mat

description: :unav
DOI: 10.11588/data/veeidp/p04rh3
title: BZ64_7_160921_17_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/7e6rm8
title: BZ64_7_Block_6_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/9b8kk6
title: BZ64_6_Block_7_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/fegc7x
title: BZ64_8_160921_14_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/q8twi8
title: Same State_distribution plot.pdf

description: :unav
DOI: 10.11588/data/veeidp/cgulpt
title: BZ64_6_Block_6_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/rdtgzp
title: Firing_Rate_Neurons_COMBINED.m

description: :unav
DOI: 10.11588/data/veeidp/5ohxlp
title: SampleTimes.tab

description: :unav
DOI: 10.11588/data/veeidp/fbvt34
title: BZ64_4_161005_19_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/tmtmda
title: BZ64_6_160921_18_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/vfei4p
title: BZ64_6_Block_5_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/fd1b7r
title: Unit_Rate_Global_Internal_Permutation_Test_473.mat

description: :unav
DOI: 10.11588/data/veeidp/fis5nm
title: BZ64_6_161005_19_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/njdtb1
title: permutationTest.m

description: :unav
DOI: 10.11588/data/veeidp/xqm0co
title: BZ64_7_160921_14_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/sudosp
title: Same_State_Summary.tab

description: :unav
DOI: 10.11588/data/veeidp/fe4kgi
title: BZ64_6_161005_19_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/fbbrho
title: Same_State_UnitSpkTimes.mat

description: :unav
DOI: 10.11588/data/veeidp/ak7mkr
title: BZ64_6_Block_6_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/gcnr2j
title: BZ64_8_Block_5_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/rtl1m4
title: Unit_rate_State.m

description: :unav
DOI: 10.11588/data/veeidp/l47eoa
title: BZ64_7_161005_19_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/cm6afj
title: BZ64_8_160921_14_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/non9n0
title: pRateVariant.m

description: :unav
DOI: 10.11588/data/veeidp/vebnma
title: State_Comp_UnitSpkTimes.mat

description: :unav
DOI: 10.11588/data/veeidp/cd6pvw
title: BZ64_8_160921_17_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/uhqy4v
title: BZ64_8_160917_15_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/xfakc4
title: BlockBins.mat

description: :unav
DOI: 10.11588/data/veeidp/ayzksx
title: BZ64_7_160913_16_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/ubjjzx
title: BZ64_5_160913_16_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/pctffl
title: State_TTLs_4minBlock.mat

description: :unav
DOI: 10.11588/data/veeidp/wty0pp
title: BZ64_7_Block_6_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/3afzwj
title: BZ64_8_Block_6_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/zvbutb
title: BZ64_7_161005_19_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/ue8jrn
title: BZ64_5_Block_4_Timebins.mat

description: :unav
DOI: 10.11588/data/veeidp/ybfdic
title: BZ64_8_160921_17_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/wlsngn
title: BZ64_8_160917_15_digital.mat

description: :unav
DOI: 10.11588/data/veeidp/vxhjba
title: BZ64_5_161006_11_unit_spikeTs.mat

description: :unav
DOI: 10.11588/data/veeidp/8puzkv
title: NN-ImageJ-Fiji-Scripts.docx

description: :unav
DOI: 10.11588/data/veeidp/n2w2xz
title: RegionSelection.ijm

description: :unav
DOI: 10.11588/data/veeidp/h1mv7a
title: BackgroundSubtractionStarDist_Mask.ijm

description: :unav
DOI: 10.11588/data/veeidp/o389zn
title: CreateIntensityColorMaps_V0.ijm

description: :unav
DOI: 10.48324/dandi.000233/0.230223.0815
title: A metabolic function of the hippocampal sharp wave-ripple

description: The hippocampus has previously been implicated in both cognitive and endocrine functions. We simultaneously measured electrophysiological activity from the hippocampus and interstitial glucose concentrations in the body of freely behaving rats to identify an activity pattern that may link these disparate functions of the hippocampus. Here we report that clusters of sharp wave-ripples recorded from the hippocampus reliably predicted a decrease in peripheral glucose concentrations within about 10 min. This correlation was not dependent on circadian, ultradian or meal-triggered fluctuations, could be mimicked with optogenetically induced ripples in the hippocampus (but not in the parietal cortex) and was attenuated to chance levels by pharmacogenetically suppressing activity of the lateral septum, which is the major conduit between the hippocampus and the hypothalamus. Our findings demonstrate that a function of the sharp wave-ripple is to modulate peripheral glucose homeostasis, and offer a mechanism for the link between sleep disruption and blood glucose dysregulation in type 2 diabetes.
DOI: 10.34740/kaggle/dsv/5048876
title: Health Workforce Shortage Areas
DOI: 10.34740/kaggle/dsv/5048893
title: AutoXGB
DOI: 10.13145/bacdive134912.20211221.6
title: Psychrobacter phenylpyruvicus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134913.20211221.6
title: Aggregatibacter actinomycetemcomitans

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134914.20211221.6
title: Actinobacillus ureae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134915.20211221.6
title: Acinetobacter kyonggiensis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134916.20211221.6
title: Escherichia coli

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134917.20211221.6
title: Paenibacillus telluris

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134918.20211221.6
title: Achromobacter dolens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134919.20211221.6
title: Shigella boydii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134920.20211221.6
title: Acinetobacter nosocomialis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134921.20211221.6
title: Acinetobacter nosocomialis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134922.20211221.6
title: Acinetobacter nosocomialis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134923.20211221.6
title: Acinetobacter nosocomialis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134924.20211221.6
title: Acinetobacter nosocomialis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134925.20211221.6
title: Acinetobacter nosocomialis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134926.20211221.6
title: Acinetobacter nosocomialis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134927.20211221.6
title: Acinetobacter pittii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134928.20211221.6
title: Acinetobacter pittii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134929.20211221.6
title: Acinetobacter ursingii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive134930.20211221.6
title: Acinetobacter pittii

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.