cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ruar3d
title: Occurrence Download

description: A dataset containing 196 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Diabrotica undecimpunctata Jacoby, 1879",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 196 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085208-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8ag32x
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Hilara setosa Collin, 1927",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085210-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c4nkxm
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lepilemur septentrionalis Rumpler & Albignac, 1975)",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2000",
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 100",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085211-240626123714530/datasets/export for details.
DOI: 10.15468/dl.g7x2pb
title: Occurrence Download

description: A dataset containing 334 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calothamnus Labill."
 ]
}

 The dataset includes 334 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085212-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cnnczc
title: Occurrence Download

description: A dataset containing 196 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Diabrotica undecimpunctata Jacoby, 1879",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 196 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085213-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pzquj7
title: Occurrence Download

description: A dataset containing 56903 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Liriodendron tulipifera L."
 ]
}

 The dataset includes 56903 records from 562 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085209-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t7wp9m
title: Occurrence Download

description: A dataset containing 465174267 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tracheophyta"
 ]
}

 The dataset includes 465174267 records from 14632 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085174-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23728/b2share.a815cf4ac302405e8671af577c7aa8f8
title: Air quality data from the LIFE+RESPIRA project in Pamplona, Spain: humidity in 2015 (16h UTC) (interpolated GeoTIFF)

description: GeoTIFF file including interpolated air quality data from the LIFE+RESPIRA project (http://www.liferespira.eu/) in Pamplona, Spain, with measures of humidity during 2015, aggregated by hour (16h UTC).
DOI: 10.15468/dl.ch77yh
title: Occurrence Download

description: A dataset containing 624617 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lythrum salicaria L."
 ]
}

 The dataset includes 624617 records from 2710 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047187-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/o6o04o/p4ghtn
title: Compensation Controls_BV421 Stained Control_008.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/sdigbf
title: Compensation Controls_PE Stained Control_025.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/ywyhv3
title: Compensation Controls_Unstained Control_016.fcs

description: :unav
DOI: 10.5281/zenodo.3627048
title: Scaled counts of trichome mRNA-seq from the 20 accessions

description: <strong>mRNA-seq scaled counts from stem trichomes of the 20 accessions. </strong> Pipeline: rnaseq-analysis-kallisto-sleuth: release v0.2.2 https://github.com/BleekerLab/rnaseq-analysis-kallisto-sleuth/releases Transcriptome used: S. lycopersicum ITAG4.0 cDNA <strong>Table of genotypes</strong> <pre><code class="language-markdown">| accession | species | accession nr | synonym | origin | |------------|--------------------------------|--------------|---------|-------------| | LA2172 | S. arcanum | TR0009 | - | Peru | | LA1401* | S. cheesmaniae f. minor | EA00652 | - | Ecuador | | LA1840 | S. chmielewskii | - | - | unknown | | LA2695 | S. chmielewskii | EA00759 | - | Peru | | LA0407 | S. habrochaites f. glabratum | EA00558 | - | Ecuador | | LA1777 | S. habrochaites f. hirsutum | EA00703 | - | Peru | | PI134418 | S. habrochaites f. glabratum | TR00015 | LYC38 | unknown | | LYC4 | S. habrochaites f. hirsutum | TR00017 | - | unknown | | LA1718 | S. habrochaites f. glabratum | EA00699 | LYC4934 | Peru | | PI127826 | S. habrochaites f. hirsutum | - | - | Peru | | LA1364 | S. huaylasense | TR00030 | - | Peru | | Moneymaker | S. lycopersicum | - | C32 | Netherlands | | LA4024 | S. lycopersicum | TA209 | - | unknown | | LA2133 | S. neorickii/L. parviflorum | EA00729 | - | Peru | | LA0735 | S. neorickii | TR00025 | LYC140 | unknown | | LA0716 | S. pennellii | EA00585 | - | Peru | | LA1278 | S. peruvianum/pimpinellifolium | TR00005 | - | unknown | | LA1954 | S. peruvianum | EA00713 | - | Peru | | LA1578 | S. pimpinellifolium | EA00674 | - | Peru |</code></pre>
description: Stem trichome mRNA-seq scaled estimates
DOI: 10.5281/zenodo.3627049
title: Scaled counts of trichome mRNA-seq from the 20 accessions

description: <strong>mRNA-seq scaled counts from stem trichomes of the 20 accessions. </strong> Pipeline: rnaseq-analysis-kallisto-sleuth: release v0.2.2 https://github.com/BleekerLab/rnaseq-analysis-kallisto-sleuth/releases Transcriptome used: S. lycopersicum ITAG4.0 cDNA <strong>Table of genotypes</strong> <pre><code class="language-markdown">| accession | species | accession nr | synonym | origin | |------------|--------------------------------|--------------|---------|-------------| | LA2172 | S. arcanum | TR0009 | - | Peru | | LA1401* | S. cheesmaniae f. minor | EA00652 | - | Ecuador | | LA1840 | S. chmielewskii | - | - | unknown | | LA2695 | S. chmielewskii | EA00759 | - | Peru | | LA0407 | S. habrochaites f. glabratum | EA00558 | - | Ecuador | | LA1777 | S. habrochaites f. hirsutum | EA00703 | - | Peru | | PI134418 | S. habrochaites f. glabratum | TR00015 | LYC38 | unknown | | LYC4 | S. habrochaites f. hirsutum | TR00017 | - | unknown | | LA1718 | S. habrochaites f. glabratum | EA00699 | LYC4934 | Peru | | PI127826 | S. habrochaites f. hirsutum | - | - | Peru | | LA1364 | S. huaylasense | TR00030 | - | Peru | | Moneymaker | S. lycopersicum | - | C32 | Netherlands | | LA4024 | S. lycopersicum | TA209 | - | unknown | | LA2133 | S. neorickii/L. parviflorum | EA00729 | - | Peru | | LA0735 | S. neorickii | TR00025 | LYC140 | unknown | | LA0716 | S. pennellii | EA00585 | - | Peru | | LA1278 | S. peruvianum/pimpinellifolium | TR00005 | - | unknown | | LA1954 | S. peruvianum | EA00713 | - | Peru | | LA1578 | S. pimpinellifolium | EA00674 | - | Peru |</code></pre>
description: Stem trichome mRNA-seq scaled estimates
DOI: 10.6073/pasta/23161f1bba07248c558a2ef0e4c914f4
title: Determinative factors of denitrification in a urban, arid wash of central Arizona (2012-2013)

description: Although the absence of nitrogen (N) can be detrimental to many biological processes, in large quantities certain forms of N can be harmful to the environment. N deposits can leak down through the soil and accumulate in groundwater stores, lakes, and other bodies of water. In arid, residential watersheds, N accumulates by fertilization, atmospheric deposition, and litter from residents and is transported to washes during storms. The main goal of this research is to ascertain how geochemical and hydrological factors limit denitrification and, therefore, affect the quantities of N exported from such a wash. In this study, we evaluate the effects of factors including moisture content, soil texture, and N concentrations on denitrification in a residential, desert wash. In order to carry out our research, we sampled soil from a wash in Scottsdale, AZ during summer 2012. Although there were no strong geochemical correlations with denitrification, it was found that there was a strong relationship between denitrification and distance between inlets and sites.
DOI: 10.7910/dvn/o6o04o/9vn4q2
title: -SED -2-5h inc_2) Iso-T+JY PDL1_2_002.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/fgecma
title: Compensation Controls_Alexa Fluor 488 Stained Control_013.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/hqbroy
title: Compensation Controls_BV421 Stained Control_023.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/isvlcs
title: Ir time course_5-JY PDL1 PDL1-T Ir 10min_005.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/s4kobl
title: PDL1-T HRP 30sec_2-PDL1-T_002.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/sfcsnn
title: PDL1-T HRP 30sec_Unst Jurkat PD1_006.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/tcyykt
title: Ir time course_6-FMO-AF488_006.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/wotq0e
title: JY PDL1-T+Jurkat_Ir time course_PDL1-T 10min_005.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/wz6qdz
title: + +_Iso_2_016.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/8fges6
title: Ir time course_Unst Jurkat PD1_009.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/e3unjf
title: Ir 10min_6-Jurkat CD45RO-T Ir 10min_006.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/farcul
title: + +_FMO-AF488_021.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/hzmyxz
title: PD1_Ir_PD1 2min 1_004.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/mcmzjv
title: PDL1-T HRP 30sec_3-FMO-AF488_003.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/q5ksn2
title: PD1_Ir_Jurkat PD1_015.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/tqah9g
title: Jurkat CD45RO-T_Iso-T Ir 10min 3_010.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/wfqojy
title: Compensation Controls_APC Stained Control_015.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/y2stno
title: Unstained_JY PDL1_022.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/h20g4i
title: Ir time course_2-JY PDL1 PDL1-T Ir 0min_002.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/j3fxsx
title: Ir time course_1-JY PDL1 Iso-T Ir 10min_001.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/nit8hx
title: Compensation Controls_Unstained Control_010.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/pnhqvj
title: JY PDL1-T+Jurkat_Ir time course_PDL1-T 2min_004.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/qvdear
title: Compensation Controls_PE Stained Control_010.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/st1koh
title: PD1_Ir_FMO-AF488_010.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/tyc7o3
title: -SED -2-5h inc_4) PD1-T+JY PDL1_1_004.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/winayc
title: Compensation Controls_Unstained Control_019.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/zaq3jr
title: -SED -2-5h inc_9) Iso-T+Jurkat WT_3_009.fcs

description: :unav
DOI: 10.15468/kpf1hs
title: The high complexity of Micronetinae Hull, 1920 (Araneae, Linyphiidae) evidenced through ten new cave-dweller species from the Morocco

description: This dataset contains the digitized treatments in Plazi based on the original journal article Barrientos, José Antonio, Brañas, Neus, Mederos, Jorge (2020): The high complexity of Micronetinae Hull, 1920 (Araneae, Linyphiidae) evidenced through ten new cave-dweller species from the Morocco. zoosystema 42 (1): 1-29, DOI: https://doi.org/10.5252/zoosystema2020v42a1
DOI: 10.7910/dvn/o6o04o/0tk5ic
title: Specimen_001_2-Jurkat RO-T+JY PDL1 Ir 10min_002.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/4xyfsd
title: Ir time course_2-JY PDL1-T Ir No light_002.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/6azdou
title: PD1_Ir_PD1 2min 2_005.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/aqfnfk
title: + +_FMO-APC_022.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/awsqfn
title: PD1_Ir_JY PDL1_014.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/dhfkdh
title: Ir 10min_unst JY WT_012.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/lj8xcq
title: + +_PDL1_2_019.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/lvorfu
title: Compensation Controls_PE Stained Control_014.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/yuscpb
title: JY PDL1-T Ir 10min_JY PDL1_PDL1-T Ir 10min_020.fcs

description: :unav
DOI: 10.21227/qg0z-dk23
title: Combining machine learning and metabolomics to identify weight gain biomarkers

description: This dataset was used in the article "Dias-Audibert FL, Navarro LC, de Oliveira DN, Delafiori J, Melo CFOR, Guerreiro TM, Rosa FT, Petenuci DL, Watanabe MAE, Velloso LA, Rocha AR and Catharino RR (2020) Combining Machine Learning and Metabolomics to Identify Weight Gain Biomarkers. Front. Bioeng. Biotechnol. 8:6. doi: 10.3389/fbioe.2020.00006", open access available at: https://doi.org/10.3389/fbioe.2020.00006.Article abstract:Weight gain is a metabolic disorder that often culminates in the development of obesity and other comorbidities such as diabetes. Obesity is characterized by the development of a chronic, subclinical systemic inflammation, and is regarded as a remarkably important factor that contributes to the development of such comorbidities. Therefore, laboratory methods that allow the identification of subjects at higher risk for severe weight-associated morbidity are of utter importance, considering the health and safety of populations. This contribution analyzed the plasma of 180 Brazilian individuals, equally divided into a eutrophic control group and case group, to assess the presence of biomarkers related to weight gain, aiming at characterizing the phenotype of this population. Samples were analyzed by mass spectrometry and most discriminant features were determined by a machine learning approach using Random Forest algorithm. Five biomarkers related to the pathogenesis and chronicity of inflammation in weight gain were identified. Two metabolites of arachidonic acid were upregulated in the case group, indicating the presence of inflammation, as well as two other molecules related to dysfunctions in the cycle of nitric oxide (NO) and increase in superoxide production. Finally, a fifth case group marker observed in this study may indicate the trigger for diabetes in overweight and obesity individuals. The use of mass spectrometry combined withmachine learning analyses to prospect and characterize biomarkers associated with weight gain will pave the way for elucidating potential therapeutic and prognostic targets.
DOI: 10.7910/dvn/o6o04o/7fmptd
title: JY PDL1-T+Jurkat_Ir time course_FMO-APC_007.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/ckri4f
title: 30sec_JY PDL1-T FMO-APC CD19_008.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/cpjgic
title: Compensation Controls_Alexa Fluor 488 Stained Control_012.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/ixvv61
title: JY PDL1-T Ir 10min_JY PDL1_Iso-T Ir 10min_019.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/kt7hnu
title: Compensation Controls_Unstained Control_011.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/l91xhp
title: Compensation Controls_BV421 Stained Control_011.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/ntrgrc
title: PD1_Ir_PD1 10min 1_007.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/ufbyk7
title: Compensation Controls_APC Stained Control_014.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/uxv7yz
title: Specimen_001_8-FMO-APC HRP_008.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/wezgtt
title: + +_Iso_3_017.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/7nppyn
title: -SED -2-5h inc_10) PD1-T+Jurkat WT_1_010.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/arvaqd
title: Ir time course_1-JY Iso-T Ir 10min_001.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/hlrfsw
title: Compensation Controls_Alexa Fluor 488 Stained Control_012.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/kbtdpv
title: -SED -2-5h inc_Unstained Jurkat PD1_013.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/qye8nj
title: + +_Iso_1_015.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/tb79pa
title: PDL1-T HRP 30sec_4-FMO-APC_004.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/vzyifk
title: Ir time course_Unst JY PDL1_008.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/4yht2h
title: PD1_Ir_Iso 10min 3_003.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/bqgcjf
title: -SED -2-5h inc_7) Iso-T+Jurkat WT_1_007.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/is5xnh
title: - -_Iso_2_002.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/juf7w6
title: Compensation Controls_APC Stained Control_026.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/mpwj8d
title: - -_FMO-APC_007.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/r6op6r
title: + +_PDL1_1_018.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/tekyln
title: Compensation Controls_Alexa Fluor 488 Stained Control_012.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/zwolcj
title: Compensation Controls_PE Stained Control_013.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/3ktacp
title: Ir time course_7-FMO-APC_007.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/68yexc
title: -SED -2-5h inc_6) PD1-T+JY PDL1_3_006.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/9f5gsu
title: Ir 10min_5-Jurkat Iso-T Ir 10min_005.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/fdev1e
title: Jurkat CD45RO-T_RO-T Ir 10min 2_012.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/h1nxr0
title: Compensation Controls_BV421 Stained Control_012.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/lo3i1d
title: Jurkat CD45RO-T_RO-T Ir FMO-AF488_017.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/nerpcq
title: Ir v HRP_Unst JY PDL1_010.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/pyvmos
title: Specimen_001_4-Jurkat RO-T+JY PDL1 HRP 30sec_004.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/tpzseo
title: Jurkat CD45RO-T_Iso-T Ir 10min 1_008.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/ulek2i
title: Compensation Controls_Unstained Control_010.fcs

description: :unav
DOI: 10.5281/zenodo.3627091
title: Scaled counts of trichome mRNA-seq from the 20 accessions

description: <strong>mRNA-seq scaled counts from stem trichomes of the 20 accessions. </strong> Pipeline: rnaseq-analysis-kallisto-sleuth: release v0.2.2 https://github.com/BleekerLab/rnaseq-analysis-kallisto-sleuth/releases Transcriptome used: S. lycopersicum ITAG4.0 cDNA <strong>Table of genotypes</strong> <pre><code class="language-markdown">| accession | species | accession nr | synonym | origin | |------------|--------------------------------|--------------|---------|-------------| | LA2172 | S. arcanum | TR0009 | - | Peru | | LA1401* | S. cheesmaniae f. minor | EA00652 | - | Ecuador | | LA1840 | S. chmielewskii | - | - | unknown | | LA2695 | S. chmielewskii | EA00759 | - | Peru | | LA0407 | S. habrochaites f. glabratum | EA00558 | - | Ecuador | | LA1777 | S. habrochaites f. hirsutum | EA00703 | - | Peru | | PI134418 | S. habrochaites f. glabratum | TR00015 | LYC38 | unknown | | LYC4 | S. habrochaites f. hirsutum | TR00017 | - | unknown | | LA1718 | S. habrochaites f. glabratum | EA00699 | LYC4934 | Peru | | PI127826 | S. habrochaites f. hirsutum | - | - | Peru | | LA1364 | S. huaylasense | TR00030 | - | Peru | | Moneymaker | S. lycopersicum | - | C32 | Netherlands | | LA4024 | S. lycopersicum | TA209 | - | unknown | | LA2133 | S. neorickii/L. parviflorum | EA00729 | - | Peru | | LA0735 | S. neorickii | TR00025 | LYC140 | unknown | | LA0716 | S. pennellii | EA00585 | - | Peru | | LA1278 | S. peruvianum/pimpinellifolium | TR00005 | - | unknown | | LA1954 | S. peruvianum | EA00713 | - | Peru | | LA1578 | S. pimpinellifolium | EA00674 | - | Peru |</code></pre>
description: Stem trichome mRNA-seq scaled estimates
DOI: 10.7910/dvn/o6o04o/3ofajp
title: Compensation Controls_BV421 Stained Control_017.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/duqpmi
title: Compensation Controls_BV421 Stained Control_014.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/e1dbyd
title: Jurkat CD45RO-T_RO-T Ir 10min 1_011.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/ev2fd4
title: Ir 10min_8-FMO-AF488_008.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/ko6sjh
title: Ir 10min_unst JY PDL1_010.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/rgcwba
title: Ir v HRP_3-Jurkat Iso-T+JY PDL1 HRP 30sec_003.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/w2xuvf
title: Ir time course_6-FMO-AF488_006.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/wexgww
title: JY PDL1-T+Jurkat_Ir time course_FMO-AF488_006.fcs

description: :unav
DOI: 10.7910/dvn/o6o04o/yo99mx
title: - -_PDL1_2_005.fcs

description: :unav