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76 results for “brassinosteroids”

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zenodo40/100

Figure 7 in Mitigation of the effects of salt stress in cowpea bean through the exogenous aplication of brassinosteroid

Figure 7. Effect of 24-epibrasinolide in the activity of the enzyme nitrate reductase of cowpea roots under salt stress. Capital letters indicate statistical differences between EBL treatments (p <0.05) based on upon a Tukey's test; small letters indicate statistical differences between salt treatments (p <0.05) based on upon a Tukey's test.

opencc-by-4.0Dec 2022View details →

zenodo40/100

Figure 6 in Mitigation of the effects of salt stress in cowpea bean through the exogenous aplication of brassinosteroid

Figure 6. Effect of 24-epibrasinolide in the activity of the enzyme nitrate reductase of cowpea leaves under salt stress. Capital letters indicate statistical differences between EBL treatments (p <0.05) based on upon a Tukey's test; small letters indicate statistical differences between salt treatments (p <0.05) based on upon a Tukey's test.

opencc-by-4.0Dec 2022View details →

zenodo40/100

Figure 3 in Mitigation of the effects of salt stress in cowpea bean through the exogenous aplication of brassinosteroid

Figure 3. Effect of 24-epibrasinolide in the stem diameter of cowpea plants under salt stress. Capital letters indicate statistical differences between EBL treatments (p <0.05) based on upon a Tukey's test; small letters indicate statistical differences between salt treatments (p <0.05) based on upon a Tukey's test.

opencc-by-4.0Dec 2022View details →

dryad40/100

Data from: The brassinosteroid receptor gene BRI1 safeguards cell-autonomous brassinosteroid signaling across tissues

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publicSep 2024View details →

zenodo36/100

Untargeted mutagenesis of brassinosteroid receptor SbBRI1 confers drought tolerance by altering phenylpropanoid metabolism in Sorghum bicolor

Metabolomics data from the study: Untargeted mutagenesis of brassinosteroid receptor SbBRI1 confers drought tolerance by altering phenylpropanoid metabolism in Sorghum bicolor. Files are raw chromatograms. Metabolite profiling analysis Metabolite Extraction and Quantification. The whole metabolite extraction and quantification pipeline followed the guidelines as described in Giavalisco et al. (2011) and Salem et al. (2020). Briefly, 10-25 mg of fresh plant tissue was harvested and immediately frozen in N2, and ground using zirconia beads with the help of Tissue Lyser Mixer-Mill (Qiagen) 3 min at 25 Hz. After samples were extracted in 100% cold methanol, they were centrifuged for 10 min at 14000 rpm (Room temperature) and 3:1 chloroform was added. After vortexing thoroughly, 1:1 volume of water was added and the samples were subsequently vortexed and centrifuged. The semi-polar phase was used for analysis of semi-polar secondary and primary metabolites. For secondary semi-polar metabolites, the dried polar aliquots were resuspended in water:methanol (1:1 v/v). 3 Analysis of semi-polar metabolites was performed using a Thermo Q Exactive Focus coupled to a reverse-phase C18 column. The column was maintained at 40°C with a flow rate of 400 μl/min, and the eluent system consisted of water (eluent A) and acetonitrile (eluent B), both containing 0.1% formic acid. Mass spectra were acquired in full scan mode over a range of 100-1500 m/z using data-independent acquisition (DIA) with high-energy collisional dissociation (HCD) energy set at 30 eV in positive mode. 9 For primary metabolite metabolites, the dried polar was derivatized as described in Lisec et al. (2006). Derivatization was carried out at 37°C for 120 min using 40 μl of 20 mg/ml methoxyamine hydrochloride in pyridine, followed by a 30-min treatment at 37°C with 70 μl of trimethylsilyl-N-methyl trifluoroacetamide (MSTFA). The derivatized samples (1 μl) were injected in splitless mode into a gas chromatograph coupled to a time-of-flight mass spectrometer (Pegasus HT TOF-MS). Gas chromatography was performed on a 30-m DB-35 column using helium as the carrier gas. The initial temperature of the oven was 85°C, and it was ramped up at a rate of 15°C/min to a final temperature of 360°C. Mass spectra were recorded in the range of 70-600 m/z at a rate of 20 scans/s. Data Processing and Compound Annotation. LC-MS full scan data were processed using MS Refiner (Expressionist 14.0). Processing of chromatograms, peak detection, and integration were performed using RefinerMS (version 5.3; GeneData). Metabolite identification and annotation were performed using in-house reference compound library, tandem MS (MS/MS) 22 fragmentation, and metabolomics databases (Alseekh et al., 2021). For the annotation of metabolites measured by GC-MS the Golm Metabolome Database was used (Kopka et al., 2005). <div> <div> #heatmap of fold changes  </div> <div> ts <-read.csv("all_log2fc_heat_all.csv", sep=";", fileEncoding='latin1',check.names=F, header=TRUE)  </div> <div> ts1 <- ts  </div> <div> ts1$class <- NULL   </div> <div>   </div> <div> row.names(ts1) <- ts1$compound  </div> <div> ts1$compound <- NULL  </div> <div> m <- as.matrix(ts1)  </div> <div>   </div> <div> ann <- ts[1:2]  </div> <div> row.names(ann) <- ann$compound  </div> <div> ann$compound <- NULL  </div> <div>   </div> <div> install.packages("pheatmap")  </div> <div>   </div> <div> library("pheatmap")  </div> <div>   </div> <div> m1 <- m[rownames(ann), ]  </div> <div>   </div> <div> pheatmap(m1, annotation_row = ann, cluster_rows = F,cluster_cols = F, cellheight = 10,   </div> <div>          cellwidth = 10, gaps_row = cumsum(c(3,105,30,11,21,4,32,5,17)), gaps_col = cumsum(c(2,2,2)), scale = 'none')  </div> <div>   </div> <div> #boxplots  </div> <div> install.packages("ggplot2")  </div> <div> install.packages("readr")  </div> <div>   </div> <div> library(ggplot2)  </div> <div> library(readr)  </div> <div>   </div> <div> install.packages("tidyverse")  </div> <div> library(tidyverse)  </div> <div> grid <- read.csv("sec_exp1_logfc_20.csv", sep=";", header=TRUE)  </div> <div>   </div> <div> grid_g <- grid%>% gather("compound", "value", 6:25)  </div> <div>   </div> <div> d=ggplot(data = grid_g, aes(x=compound, y=value, fill=factor(group)))+  </div> <div>   geom_boxplot(outlier.shape = NA)+  </div> <div>   geom_point(position = position_jitterdodge(0.1))  </div> <div>   </div> <div> d+theme(text = element_text(size = 15))+  </div> <div>   scale_fill_manual(values = c("#ca5826","#e4ab92", "#008080", "#99cccc"))+  </div> <div>   labs(y="log2fc(metabolite content)",fill="gtype")+  </div> <div>   theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 5)) +   </div> <div>   theme_classic() +  </div> <div>   coord_flip() +  </div> <div>   facet_grid(condition ~ .)  </div> <div>   </div> <div> ggsave("logfcsum_exp1_15_bri1.png", width = 10, height = 10)  </div> <div>   </div> <div> #boxplots all data  </div> <div> library(ggplot2)  </div> <div> library(readr)  </div> <div> library(viridis)  </div> <div> library(tidyverse)  </div> <div> library(dplyr)  </div> <div>   </div> <div> sPCA <-read.csv("GCMS_polar.csv", sep=",", fileEncoding='latin1', check.names = F, header=TRUE)  </div> <div>   </div> <div> row.names(sPCA) <- sPCA$Sample  </div> <div> sPCA_D <- sPCA[6:155]  </div> <div> sPCA_Dlog <- log(sPCA_D)  </div> <div> sPCA_Dlog10 <- log10(sPCA_D)  </div> <div>   </div> <div> sPCA_Dlog <- cbind(sPCA_Dlog, group = sPCA$Sample_group)  </div> <div> sPCA_Dlog <- sPCA_Dlog%>% select(group, everything())  </div> <div>   </div> <div> sPCA_Dlog <- cbind(sPCA_Dlog, sample = sPCA$Sample)  </div> <div> sPCA_Dlog <- sPCA_Dlog%>% select(sample, everything())  </div> <div>   </div> <div> write.csv(sPCA_Dlog10, "GCMS_polar_lg.csv")  </div> <div>   </div> <div> sPCA_Dlog_g <- sPCA_Dlog%>% gather("compound", "value", 3:152)  </div> <div>   </div> <div> d <- ggplot(sPCA_Dlog_g, aes(x=sample, y=value, fill=factor(group)))+  </div> <div>   geom_boxplot(outlier.shape = NA)+  </div> <div>   geom_point(position = position_jitterdodge(0.1))  </div> <div>   </div> <div> d + theme(text = element_text(size = 15))+  </div> <div>   scale_fill_manual(values = c("#CC6677","#882255","#44AA99", "#117733"))+  </div> <div>   labs(y="lg(normalized metabolite content)", x= "sample" , fill="group")+  </div> <div>   theme(axis.text.x = element_text(angle = 60, hjust = 1)) +   </div> <div>   theme_classic() +  </div> <div>   geom_hline(yintercept=0, linetype="dashed", color = "black")  </div> <div> #PCA  </div> <div> install.packages("plotly")  </div> <div> install.packages("ggfortify")  </div> <div> library(plotly)  </div> <div> library(ggfortify)  </div> <div>   </div> <div> sPCA <-read.csv("prim.csv", sep=";", header=TRUE)  </div> <div>   </div> <div> sPCA <- subset(sPCA, experiment!="2")  </div> <div>   </div> <div> sPCAtd <- all_d[7:240]  </div> <div> sPCAtdn <- sPCAtd[-c(24), ]  </div> <div> sPCAn <- sPCA[-c(24), ]  </div> <div>   </div> <div> #normal  </div> <div>   </div> <div> sec.pcat <- prcomp(sPCAtd, center = TRUE,scale. = TRUE)  </div> <div>   </div> <div> summary(sec.pcat)  </div> <div>   </div> <div> p <- autoplot(sec.pcat, data = all_d, colour = 'condition', shape = 'Genotype') +   </div> <div>   geom_text(aes(label = Replicate), nudge_y = 0.02) +  </div> <div>   theme_classic() +  </div> <div>   scale_color_manual(values=c("#56B4E9", "#E69F00"))  </div> <div>   </div> <div> ggplotly(p)  </div> <div> #experiment wise fold changes  </div> <div> write.csv(sec_fc_mean, "sec_foldchange_mean.csv")  </div> <div>   </div> <div> sec_fc_exp1 <- sect[1]  </div> <div>   </div> <div> sec_fc_exp1$bri1.drought <- foldchange(sect$X72.bri1.drought, sect$median.WT.c1)  </div> <div> sec_fc_exp1$bri1.drought1 <- foldchange(sect$X72.bri1.drought.1, sect$median.WT.c1)  </div> <div> sec_fc_exp1$bri1.drought2 <- foldchange(sect$X72.bri1.drought.2, sect$median.WT.c1)  </div> <div>   </div> <div> sec_fc_exp1$bri1.control <- foldchange(sect$X72.bri1.control, sect$median.WT.c1)  </div> <div> sec_fc_exp1$bri1.control1 <- foldchange(sect$X72.bri1.control.1, sect$median.WT.c1)  </div> <div> sec_fc_exp1$bri1.control2 <- foldchange(sect$X72.bri1.control.2, sect$median.WT.c1)  </div> <div>   </div> <div> sec_fc_exp1$WT.drought <- foldchange(sect$X72.WT..drought, sect$median.WT.c1)  </div> <div> sec_fc_exp1$WT.drought1 <- foldchange(sect$X72.WT..drought.1, sect$median.WT.c1)  </div> <div> sec_fc_exp1$WT.drought2 <- foldchange(sect$X72.WT..drought.2, sect$median.WT.c1)  </div> <div>   </div> <div> sec_fc_exp1$WT.control <- foldchange(sect$X72.WT..control, sect$median.WT.c1)  </div> <div> sec_fc_exp1$WT.control1 <- foldchange(sect$X72.WT..control.1, sect$median.WT.c1)  </div> <div> sec_fc_exp1$WT.control2 <- foldchange(sect$X72.WT..control.2, sect$median.WT.c1)  </div> <div>   </div> <div>   </div> <div> write.csv(sec_fc_exp1, "sec_fc_exp1.csv")  </div> <div>   </div> <div> #all compounds for RNAsq comarision  </div> <div>   </div> <div> all_R <-read.csv("all_RNAsq.csv", sep=";", fileEncoding='latin1',check.names=F, header=T)  </div> <div>   </div> <div> all_fc_exp2 <- all_R[1]  </div> <div>   </div> <div> all_fc_exp2$drought <- foldchange(all_R$bri1_drought, all_R$WT_drought)  </div> <div>   </div> <div> all_fc_exp2$control <- foldchange(all_R$bri1_control, all_R$WT_control)  </div> <div>   </div> <div> write.csv(all_fc_exp2, "all_foldchange_exp2.csv")  </div> <div>   </div> <div> #students t test  </div> <div>   </div> <div> secfc_2_t <-read.csv("sec_exp1_logfc.csv", sep=";", fileEncoding='latin1',check.names=F, header=T)  </div> <div>   </div> <div> secfc_2_t <- secfc_2_t[-2]  </div> <div> secfc_2_t <- secfc_2_t[-(14:25)]  </div> <div>   </div> <div> st2<- secfc_2_t %>% gather("compound", "value", 6:171)  </div> <div> stat.test1 <- st2 %>%  </div> <div>   group_by(compound) %>%  </div> <div>   t_test(value ~ group)  </div> <div> add_significance()  </div> <div> stat.test1  </div> </div>

opencc-by-4.0Jul 2024View details →

zenodo36/100

Brassinosteroid gene regulatory networks at cellular resolution in the Arabidopsis root

Supplemental datasets for "Brassinosteroid gene regulatory networks at cellular resolution in the Arabidopsis root".

opencc-by-4.0Dec 2022View details →

dryad32/100

Data from: The clathrin adaptor complex AP-2 mediates endocytosis of BRASSINOSTEROID INSENSITIVE1 in Arabidopsis

Clathrin-mediated endocytosis (CME) regulates many aspects of plant development, including hormone signaling and responses to environmental stresses. Despite the importance of this process, the machinery that regulates CME in plants is largely unknown. In mammals, the heterotetrameric ADAPTOR PROTEIN COMPLEX-2 (AP-2) is required for the formation of clathrin-coated vesicles at the plasma membrane (PM). Although the existence of AP-2 has been predicted in Arabidopsis thaliana, the biochemistry and functionality of the complex is still uncharacterized. Here, we identified all the subunits of the Arabidopsis AP-2 by tandem affinity purification and found that one of the large AP-2 subunits, AP2A1, localized at the PM and interacted with clathrin. Furthermore, endocytosis of the leucine-rich repeat receptor kinase, BRASSINOSTEROID INSENSITIVE1 (BRI1), was shown to depend on AP-2. Knockdown of the two Arabidopsis AP2A genes or overexpression of a dominant-negative version of the medium AP-2 subunit, AP2M, impaired BRI1 endocytosis and enhanced the brassinosteroid signaling. Our data reveal that the CME machinery in Arabidopsis is evolutionarily conserved and that AP-2 functions in receptor-mediated endocytosis.

opencc-zeroDec 2012View details →

dryad32/100

Raw data for: Phosphate deprivation-induced changes in tomato are mediated by an interaction between brassinosteroid signaling and zinc

Open the record for dataset details and reuse information.

publicMay 2023View details →

dryad32/100

Data from: The clathrin adaptor complex AP-2 mediates endocytosis of BRASSINOSTEROID INSENSITIVE1 in Arabidopsis

Open the record for dataset details and reuse information.

publicAug 2013View details →

dryad32/100

Data from: Brassinosteroids act as a positive regulator of NBR1-dependent selective autophagy in response to chilling stress in tomato

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publicDec 2019View details →

dryad28/100

Transcriptome for: MYB42 inhibits hypocotyl cell elongation by coordinating brassinosteroid homeostasis and signaling in Arabidopsis

The precise control of brassinosteroids (BRs) homeostasis and signaling is a prerequisite for hypocotyl cell elongation in plants. Little is known, however, of such regulators of BR homeostasis and signaling. Here, we have demonstrated that MYB42 negatively regulates hypocotyl elongation through partial inhibition of BRASSINAZOLE-RESISTANT 1 (BZR1) signaling and promotion of BR inactivation. Transgenic Arabidopsis plants repressing the expression of MYB42 and its paralog MYB85 (MYB85 RNAi;myb42) exhibited longer hypocotyls than wild-type (WT) plants in darkness, while MYB42 or MYB85 overexpression inhibits hypocotyl elongation. Hypocotyl length of MYB85 RNAi;myb42 plants can be resorted into WT level by MYB42 overexpression. MYB42 inhibits hypocotyl elongation by mediating BR signaling, because MYB42 expression is repressed with BR treatment and in the dominant BR mutant bzr1-1D, and mutation of both MYB42 and MYB85 enhances the dwarf phenotype of the BR receptor mutant bri1-5. BZR1 directly represses MYB42 expression in response to BR, and the hypocotyl length of bzr1-1D is reduced in MYB42 overexpression plants but increased in MYB85 RNAi;myb42 plants. These results show MYB42 is a negative target of BZR1. Transcriptome data revealed that a number of BZR1-induced genes associated with cell elongation are down-regulated by MYB42, suggesting that MYB42 may partially inhibit BZR1 signaling. In addition, MYB42 enlarges its action in BR signaling through feedback activation of the BR-inactivating enzyme DOGT1. The present study shows a MYB42-mediated multilevel system that contributes to fine regulation of BR-induced hypocotyl elongation.

opencc-zeroJan 2022View details →

dryad28/100

RIP2 interacts with REL1 to control leaf architecture by modulating brassinosteroid signaling in rice

FPKM (Fragments per kilobase of exon model per million mapped fragments) value of all detected genes in in WT, rel1, rip2, and rel1 rip2 mutants. ZH11_1, ZH11_2, ZH11_3 represent samples were collected from ZH11 with three independent biological replicates. rel1_1, rel1_2, rel1_3 represent samples were collected from rel1 mutants with three independent biological replicates. rip2_1, rip2_2, rip2_3 represent samples were collected from rip2 mutant with three independent biological replicates. rel1rip2_1, rel1rip2_2, rel1rip2_3 represent samples were collected from rel1rip2 double mutant with three independent biological replicates.

opencc-zeroJan 2022View details →

zenodo28/100

Figure 2 in Mitigation of the effects of salt stress in cowpea bean through the exogenous aplication of brassinosteroid

Figure 2. Effect of 24-epibrasinolide in the number of leaves of cowpea plants under salt stress. Capital letters indicate statistical differences between EBL treatments (p <0.05) based on upon a Tukey's test; small letters indicate statistical differences between salt treatments (p <0.05) based on upon a Tukey's test.

opencc-by-4.0Dec 2022View details →

zenodo28/100

Figure 1 in Mitigation of the effects of salt stress in cowpea bean through the exogenous aplication of brassinosteroid

Figure 1. Effect of 24-epibrasinolide in the height of cowpea plants under salt stress. Capital letters indicate statistical differences between EBL treatments (p <0.05) based on upon a Tukey's test; small letters indicate statistical differences between salt treatments (p <0.05) based on upon a Tukey's test.

opencc-by-4.0Dec 2022View details →

dryad28/100

Transcriptome for: MYB42 inhibits hypocotyl cell elongation by coordinating brassinosteroid homeostasis and signaling in Arabidopsis

Open the record for dataset details and reuse information.

publicJan 2022View details →

dryad28/100

RIP2 interacts with REL1 to control leaf architecture by modulating brassinosteroid signaling in rice

Open the record for dataset details and reuse information.

publicFeb 2022View details →

geo24/100

Interaction between BZR1 and PIF4 integrates brassinosteroid and environmental responses [RNA-seq]

GEO Series GSE37159. Arabidopsis thaliana. 8 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenJul 2012View details →

geo24/100

A single-cell morpho-transcriptomic map of brassinosteroid action in the Arabidopsis root

GEO Series GSE181178. Arabidopsis thaliana. 2 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenAug 2021View details →

geo24/100

The AP2/ERF Transcription Factor TINY Modulates Brassinosteroid-Regulated Plant Growth and Drought Response in Arabidopsis

GEO Series GSE128946. Arabidopsis thaliana. 9 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenMar 2019View details →

geo24/100

Brassinosteroid (BR) plant hormone signaling

GEO Series GSE25135. Arabidopsis thaliana. 10 samples. Type: Genome binding/occupancy profiling by genome tiling array; Expression profiling by array.

openGEO-OpenDec 2010View details →

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

International Brain Laboratory public data

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record

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Dataset results

Figure 7 in Mitigation of the effects of salt stress in cowpea bean through the exogenous aplication of brassinosteroid

Figure 6 in Mitigation of the effects of salt stress in cowpea bean through the exogenous aplication of brassinosteroid

Figure 3 in Mitigation of the effects of salt stress in cowpea bean through the exogenous aplication of brassinosteroid

Data from: The brassinosteroid receptor gene BRI1 safeguards cell-autonomous brassinosteroid signaling across tissues

Untargeted mutagenesis of brassinosteroid receptor SbBRI1 confers drought tolerance by altering phenylpropanoid metabolism in Sorghum bicolor

Brassinosteroid gene regulatory networks at cellular resolution in the Arabidopsis root

Data from: The clathrin adaptor complex AP-2 mediates endocytosis of BRASSINOSTEROID INSENSITIVE1 in Arabidopsis

Raw data for: Phosphate deprivation-induced changes in tomato are mediated by an interaction between brassinosteroid signaling and zinc

Data from: The clathrin adaptor complex AP-2 mediates endocytosis of BRASSINOSTEROID INSENSITIVE1 in Arabidopsis

Data from: Brassinosteroids act as a positive regulator of NBR1-dependent selective autophagy in response to chilling stress in tomato

Transcriptome for: MYB42 inhibits hypocotyl cell elongation by coordinating brassinosteroid homeostasis and signaling in Arabidopsis

RIP2 interacts with REL1 to control leaf architecture by modulating brassinosteroid signaling in rice

Figure 2 in Mitigation of the effects of salt stress in cowpea bean through the exogenous aplication of brassinosteroid

Figure 1 in Mitigation of the effects of salt stress in cowpea bean through the exogenous aplication of brassinosteroid

Transcriptome for: MYB42 inhibits hypocotyl cell elongation by coordinating brassinosteroid homeostasis and signaling in Arabidopsis

RIP2 interacts with REL1 to control leaf architecture by modulating brassinosteroid signaling in rice

Interaction between BZR1 and PIF4 integrates brassinosteroid and environmental responses [RNA-seq]

A single-cell morpho-transcriptomic map of brassinosteroid action in the Arabidopsis root

The AP2/ERF Transcription Factor TINY Modulates Brassinosteroid-Regulated Plant Growth and Drought Response in Arabidopsis

Brassinosteroid (BR) plant hormone signaling

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Allen Brain Atlas

Annotated Behaviour and Observability Dataset (ABODe)

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International Brain Laboratory public data

OpenNeuro

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