Searching across hundreds of databases

Our searching services are busy right now. Your search will reload in five seconds.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.

Search

Type in a keyword to search

On page 1 showing 1 ~ 20 papers out of 83 papers

The genetic architecture of type 2 diabetes.

  • Christian Fuchsberger‎ et al.
  • Nature‎
  • 2016‎

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.


Insights into islet development and biology through characterization of a human iPSC-derived endocrine pancreas model.

  • Martijn van de Bunt‎ et al.
  • Islets‎
  • 2016‎

Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at 6 stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from 2 donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs = 14.2, p-value = 4.9 × 10(-5)) and the pancreatic agenesis gene GATA6 (log2 FC = 12.1, p-value = 8.6 × 10(-5)), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to our endocrine pancreas-like cells (log2 FC = 5.5, p-value = 2.0 × 10(-12)), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. "insulin secretion"; odds ratio = 4.2, p-value = 1.9 × 10(-3)): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.


Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

  • Anubha Mahajan‎ et al.
  • PLoS genetics‎
  • 2015‎

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.


Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

  • Jason Flannick‎ et al.
  • Scientific data‎
  • 2017‎

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.


Human β cell transcriptome analysis uncovers lncRNAs that are tissue-specific, dynamically regulated, and abnormally expressed in type 2 diabetes.

  • Ignasi Morán‎ et al.
  • Cell metabolism‎
  • 2012‎

A significant portion of the genome is transcribed as long noncoding RNAs (lncRNAs), several of which are known to control gene expression. The repertoire and regulation of lncRNAs in disease-relevant tissues, however, has not been systematically explored. We report a comprehensive strand-specific transcriptome map of human pancreatic islets and β cells, and uncover >1100 intergenic and antisense islet-cell lncRNA genes. We find islet lncRNAs that are dynamically regulated and show that they are an integral component of the β cell differentiation and maturation program. We sequenced the mouse islet transcriptome and identify lncRNA orthologs that are regulated like their human counterparts. Depletion of HI-LNC25, a β cell-specific lncRNA, downregulated GLIS3 mRNA, thus exemplifying a gene regulatory function of islet lncRNAs. Finally, selected islet lncRNAs were dysregulated in type 2 diabetes or mapped to genetic loci underlying diabetes susceptibility. These findings reveal a new class of islet-cell genes relevant to β cell programming and diabetes pathophysiology.


A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

  • Alisa Manning‎ et al.
  • Diabetes‎
  • 2017‎

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.


Correlational analysis for identifying genes whose regulation contributes to chronic neuropathic pain.

  • Anna-Karin Persson‎ et al.
  • Molecular pain‎
  • 2009‎

Nerve injury-triggered hyperexcitability in primary sensory neurons is considered a major source of chronic neuropathic pain. The hyperexcitability, in turn, is thought to be related to transcriptional switching in afferent cell somata. Analysis using expression microarrays has revealed that many genes are regulated in the dorsal root ganglion (DRG) following axotomy. But which contribute to pain phenotype versus other nerve injury-evoked processes such as nerve regeneration? Using the L5 spinal nerve ligation model of neuropathy we examined differential changes in gene expression in the L5 (and L4) DRGs in five mouse strains with contrasting susceptibility to neuropathic pain. We sought genes for which the degree of regulation correlates with strain-specific pain phenotype.


Coexpression of the type 2 diabetes susceptibility gene variants KCNJ11 E23K and ABCC8 S1369A alter the ATP and sulfonylurea sensitivities of the ATP-sensitive K(+) channel.

  • Kevin S C Hamming‎ et al.
  • Diabetes‎
  • 2009‎

In the pancreatic beta-cell, ATP-sensitive K(+) (K(ATP)) channels couple metabolism with excitability and consist of Kir6.2 and SUR1 subunits encoded by KCNJ11 and ABCC8, respectively. Sulfonylureas, which inhibit the K(ATP) channel, are used to treat type 2 diabetes. Rare activating mutations cause neonatal diabetes, whereas the common variants, E23K in KCNJ11 and S1369A in ABCC8, are in strong linkage disequilibrium, constituting a haplotype that predisposes to type 2 diabetes. To date it has not been possible to establish which of these represents the etiological variant, and functional studies are inconsistent. Furthermore, there have been no studies of the S1369A variant or the combined effect of the two on K(ATP) channel function.


Electrophysiological characterisation of iPSC-derived human β-like cells and an SLC30A8 disease model.

  • Manon Jaffredo‎ et al.
  • bioRxiv : the preprint server for biology‎
  • 2023‎

iPSC-derived human β-like cells (BLC) hold promise for both therapy and disease modelling, but their generation remains challenging and their functional analyses beyond transcriptomic and morphological assessments remain limited. Here, we validate an approach using multicellular and single cell electrophysiological tools to evaluate BLCs functions. The Multi-Electrode Arrays (MEAs) measuring the extracellular electrical activity revealed that BLCs are electrically coupled, produce slow potential (SP) signals like primary β-cells that are closely linked to insulin secretion. We also used high-resolution single-cell patch-clamp measurements to capture the exocytotic properties, and characterize voltage-gated sodium and calcium currents. These were comparable to those in primary β and EndoC-βH1 cells. The KATP channel conductance is greater than in human primary β cells which may account for the limited glucose responsiveness observed with MEA. We used MEAs to study the impact of the type 2 diabetes protective SLC30A8 allele (p.Lys34Serfs*50) and found that BLCs with this allele have stronger electrical coupling. Our data suggest that with an adapted approach BLCs from pioneer protocol can be used to evaluate the functional impact of genetic variants on β-cell function and coupling.


Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes.

  • Philip Schroeder‎ et al.
  • medRxiv : the preprint server for health sciences‎
  • 2023‎

We meta-analyzed array data imputed with the TOPMed reference panel and whole-genome sequence (WGS) datasets and performed the largest, rare variant (minor allele frequency as low as 5×10-5) GWAS meta-analysis of type 2 diabetes (T2D) comprising 51,256 cases and 370,487 controls. We identified 52 novel variants at genome-wide significance (p<5 × 10-8), including 8 novel variants that were either rare or ancestry-specific. Among them, we identified a rare missense variant in HNF4A p.Arg114Trp (OR=8.2, 95% confidence interval [CI]=4.6-14.0, p = 1.08×10-13), previously reported as a variant implicated in Maturity Onset Diabetes of the Young (MODY) with incomplete penetrance. We demonstrated that the diabetes risk in carriers of this variant was modulated by a T2D common variant polygenic risk score (cvPRS) (carriers in the top PRS tertile [OR=18.3, 95%CI=7.2-46.9, p=1.2×10-9] vs carriers in the bottom PRS tertile [OR=2.6, 95% CI=0.97-7.09, p = 0.06]. Association results identified eight variants of intermediate penetrance (OR>5) in monogenic diabetes (MD), which in aggregate as a rare variant PRS were associated with T2D in an independent WGS dataset (OR=4.7, 95% CI=1.86-11.77], p = 0.001). Our data also provided support evidence for 21% of the variants reported in ClinVar in these MD genes as benign based on lack of association with T2D. Our work provides a framework for using rare variant imputation and WGS analyses in large-scale population-based association studies to identify large-effect rare variants and provide evidence for informing variant pathogenicity.


Differential CpG methylation at Nnat in the early establishment of beta cell heterogeneity.

  • Vanessa Yu‎ et al.
  • bioRxiv : the preprint server for biology‎
  • 2023‎

Beta cells within the pancreatic islet represent a heterogenous population wherein individual sub-groups of cells make distinct contributions to the overall control of insulin secretion. These include a subpopulation of highly-connected 'hub' cells, important for the propagation of intercellular Ca2+ waves. Functional subpopulations have also been demonstrated in human beta cells, with an altered subtype distribution apparent in type 2 diabetes. At present, the molecular mechanisms through which beta cell hierarchy is established are poorly understood. Changes at the level of the epigenome provide one such possibility which we explore here by focussing on the imprinted gene neuronatin (Nnat), which is required for normal insulin synthesis and secretion.


Species-specific differences in the expression of the HNF1A, HNF1B and HNF4A genes.

  • Lorna W Harries‎ et al.
  • PloS one‎
  • 2009‎

The HNF1A, HNF1B and HNF4A genes are part of an autoregulatory network in mammalian pancreas, liver, kidney and gut. The layout of this network appears to be similar in rodents and humans, but inactivation of HNF1A, HNF1B or HNF4A genes in animal models cause divergent phenotypes to those seen in man. We hypothesised that some differences may arise from variation in the expression profile of alternatively processed isoforms between species.


Evaluation of serum 1,5 anhydroglucitol levels as a clinical test to differentiate subtypes of diabetes.

  • Aparna Pal‎ et al.
  • Diabetes care‎
  • 2010‎

Assignment of the correct molecular diagnosis in diabetes is necessary for informed decisions regarding treatment and prognosis. Better clinical markers would facilitate discrimination and prioritization for genetic testing between diabetes subtypes. Serum 1,5 anhydroglucitol (1,5AG) levels were reported to differentiate maturity-onset diabetes of the young due to HNF1A mutations (HNF1A-MODY) from type 2 diabetes, but this requires further validation. We evaluated serum 1,5AG in a range of diabetes subtypes as an adjunct for defining diabetes etiology.


A panel of diverse assays to interrogate the interaction between glucokinase and glucokinase regulatory protein, two vital proteins in human disease.

  • Matthew G Rees‎ et al.
  • PloS one‎
  • 2014‎

Recent genetic and clinical evidence has implicated glucokinase regulatory protein (GKRP) in the pathogenesis of type 2 diabetes and related traits. The primary role of GKRP is to bind and inhibit hepatic glucokinase (GCK), a critically important protein in human health and disease that exerts a significant degree of control over glucose metabolism. As activation of GCK has been associated with improved glucose tolerance, perturbation of the GCK-GKRP interaction represents a potential therapeutic target for pharmacological modulation. Recent structural and kinetic advances are beginning to provide insight into the interaction of these two proteins. However, tools to comprehensively assess the GCK-GKRP interaction, particularly in the context of small molecules, would be a valuable resource. We therefore developed three robust and miniaturized assays for assessing the interaction between recombinant human GCK and GKRP: an HTRF assay, a diaphorase-coupled assay, and a luciferase-coupled assay. The assays are complementary, featuring distinct mechanisms of detection (luminescence, fluorescence, FRET). Two assays rely on GCK enzyme activity modulation by GKRP while the FRET-based assay measures the GCK-GKRP protein-protein interaction independent of GCK enzymatic substrates and activity. All three assays are scalable to low volumes in 1536-well plate format, with robust Z' factors (>0.7). Finally, as GKRP sequesters GCK in the hepatocyte nucleus at low glucose concentrations, we explored cellular models of GCK localization and translocation. Previous findings from freshly isolated rat hepatocytes were confirmed in cryopreserved rat hepatocytes, and we further extended this study to cryopreserved human hepatocytes. Consistent with previous reports, there were several key differences between the rat and human systems, with our results suggesting that human hepatocytes can be used to interrogate GCK translocation in response to small molecules. The assay panel developed here should help direct future investigation of the GCK-GKRP interaction in these or other physiologically relevant human systems.


A gating mutation at the internal mouth of the Kir6.2 pore is associated with DEND syndrome.

  • Peter Proks‎ et al.
  • EMBO reports‎
  • 2005‎

Inwardly rectifying potassium (Kir) channels control cell membrane K+ fluxes and electrical signalling in diverse cell types. Heterozygous mutations in the human Kir6.2 gene (KCNJ11), the pore-forming subunit of the ATP-sensitive (K(ATP)) channel, cause permanent neonatal diabetes mellitus. However, the I296L mutation also results in developmental delay, muscle weakness and epilepsy. We investigated the functional effects of the I296L mutation by expressing wild-type or mutant Kir6.2/SUR1 channels in Xenopus oocytes. The mutation caused a marked increase in resting whole-cell K(ATP) currents by reducing channel inhibition by ATP, in both homomeric and simulated heterozygous states. Kinetic analysis showed that the mutation impaired ATP sensitivity indirectly, by stabilizing the open state of the channel and possibly also by means of an allosteric effect on ATP binding and/or transduction. The results implicate a new region in Kir-channel gating and suggest that disease severity is correlated with the extent of reduction in ATP sensitivity.


Endocrine-Exocrine Signaling Drives Obesity-Associated Pancreatic Ductal Adenocarcinoma.

  • Katherine Minjee Chung‎ et al.
  • Cell‎
  • 2020‎

Obesity is a major modifiable risk factor for pancreatic ductal adenocarcinoma (PDAC), yet how and when obesity contributes to PDAC progression is not well understood. Leveraging an autochthonous mouse model, we demonstrate a causal and reversible role for obesity in early PDAC progression, showing that obesity markedly enhances tumorigenesis, while genetic or dietary induction of weight loss intercepts cancer development. Molecular analyses of human and murine samples define microenvironmental consequences of obesity that foster tumorigenesis rather than new driver gene mutations, including significant pancreatic islet cell adaptation in obesity-associated tumors. Specifically, we identify aberrant beta cell expression of the peptide hormone cholecystokinin (Cck) in response to obesity and show that islet Cck promotes oncogenic Kras-driven pancreatic ductal tumorigenesis. Our studies argue that PDAC progression is driven by local obesity-associated changes in the tumor microenvironment and implicate endocrine-exocrine signaling beyond insulin in PDAC development.


Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.

  • Agata Wesolowska-Andersen‎ et al.
  • eLife‎
  • 2020‎

Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict epigenome features from DNA sequence - to support inference concerning the regulatory effects of disease-associated variants. Here, we evaluate the advantages of training convolutional neural network (CNN) models on a broad set of epigenomic features collected in a single disease-relevant tissue - pancreatic islets in the case of type 2 diabetes (T2D) - as opposed to models trained on multiple human tissues. We report convergence of CNN-based metrics of regulatory function with conventional approaches to variant prioritization - genetic fine-mapping and regulatory annotation enrichment. We demonstrate that CNN-based analyses can refine association signals at T2D-associated loci and provide experimental validation for one such signal. We anticipate that these approaches will become routine in downstream analyses of GWAS.


Patterns of differential gene expression in a cellular model of human islet development, and relationship to type 2 diabetes predisposition.

  • Marta Perez-Alcantara‎ et al.
  • Diabetologia‎
  • 2018‎

Most type 2 diabetes-associated genetic variants identified via genome-wide association studies (GWASs) appear to act via the pancreatic islet. Observed defects in insulin secretion could result from an impact of these variants on islet development and/or the function of mature islets. Most functional studies have focused on the latter, given limitations regarding access to human fetal islet tissue. Capitalising upon advances in in vitro differentiation, we characterised the transcriptomes of human induced pluripotent stem cell (iPSC) lines differentiated along the pancreatic endocrine lineage, and explored the contribution of altered islet development to the pathogenesis of type 2 diabetes.


A circular RNA generated from an intron of the insulin gene controls insulin secretion.

  • Lisa Stoll‎ et al.
  • Nature communications‎
  • 2020‎

Fine-tuning of insulin release from pancreatic β-cells is essential to maintain blood glucose homeostasis. Here, we report that insulin secretion is regulated by a circular RNA containing the lariat sequence of the second intron of the insulin gene. Silencing of this intronic circular RNA in pancreatic islets leads to a decrease in the expression of key components of the secretory machinery of β-cells, resulting in impaired glucose- or KCl-induced insulin release and calcium signaling. The effect of the circular RNA is exerted at the transcriptional level and involves an interaction with the RNA-binding protein TAR DNA-binding protein 43 kDa (TDP-43). The level of this circularized intron is reduced in the islets of rodent diabetes models and of type 2 diabetic patients, possibly explaining their impaired secretory capacity. The study of this and other circular RNAs helps understanding β-cell dysfunction under diabetes conditions, and the etiology of this common metabolic disorder.


Pro-Inflammatory Cytokines Induce Insulin and Glucagon Double Positive Human Islet Cells That Are Resistant to Apoptosis.

  • Marta Tesi‎ et al.
  • Biomolecules‎
  • 2021‎

The presence of islet cells double positive for insulin and glucagon (Ins+/Glu+) has been described in the pancreas from both type 2 (T2D) and type 1 (T1D) diabetic subjects. We studied the role of pro-inflammatory cytokines on the occurrence, trajectory, and characteristics of Ins+/Glu+ cells in human pancreatic islets. Pancreas samples, isolated islets, and dispersed islet cells from 3 T1D and 11 non-diabetic (ND) multi-organ donors were studied by immunofluorescence, confocal microscopy, and/or electron microscopy. ND islet cells were exposed to interleukin-1β and interferon-γ for up to 120 h. In T1D islets, we confirmed an increased prevalence of Ins+/Glu+ cells. Cytokine-exposed islets showed a progressive increase of Ins+/Glu+ cells that represented around 50% of endocrine cells after 120h. Concomitantly, cells expressing insulin granules only decreased significantly over time, whereas those containing only glucagon granules remained stable. Interestingly, Ins+/Glu+ cells were less prone to cytokine-induced apoptosis than cells containing only insulin. Cytokine-exposed islets showed down-regulation of β-cell identity genes. In conclusion, pro-inflammatory cytokines induce Ins+/Glu+ cells in human islets, possibly due to a switch from a β- to a β-/α-cell phenotype. These Ins+/Glu+ cells appear to be resistant to cytokine-induced apoptosis.


  1. SciCrunch.org Resources

    Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.

  2. Navigation

    You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.

  3. Logging in and Registering

    If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Facets

    Here are the facets that you can filter your papers by.

  9. Options

    From here we'll present any options for the literature, such as exporting your current results.

  10. Further Questions

    If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.

Publications Per Year

X

Year:

Count: