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1.
Proc Natl Acad Sci U S A ; 119(34): e2207392119, 2022 08 23.
Artigo em Inglês | MEDLINE | ID: mdl-35969771

RESUMO

Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and technical requirements for leveraging these small but meaningful cofluctuations in the presence of measurement noise. While current technology does not yet allow adequate power for definitively detecting regulatory relationships for all TFs simultaneously in cells at steady state, we investigate a small-scale dataset to inform future experimental design. This study supports the potential value of mapping regulatory connections through stochastic variation, and it motivates further technological development to achieve its full potential.


Assuntos
Regulação da Expressão Gênica , Modelos Biológicos , Fatores de Transcrição , Simulação por Computador , Redes Reguladoras de Genes , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismo
2.
Nature ; 607(7917): 176-184, 2022 07.
Artigo em Inglês | MEDLINE | ID: mdl-35594906

RESUMO

Gene regulation in the human genome is controlled by distal enhancers that activate specific nearby promoters1. A proposed model for this specificity is that promoters have sequence-encoded preferences for certain enhancers, for example, mediated by interacting sets of transcription factors or cofactors2. This 'biochemical compatibility' model has been supported by observations at individual human promoters and by genome-wide measurements in Drosophila3-9. However, the degree to which human enhancers and promoters are intrinsically compatible has not yet been systematically measured, and how their activities combine to control RNA expression remains unclear. Here we design a high-throughput reporter assay called enhancer × promoter self-transcribing active regulatory region sequencing (ExP STARR-seq) and applied it to examine the combinatorial compatibilities of 1,000 enhancer and 1,000 promoter sequences in human K562 cells. We identify simple rules for enhancer-promoter compatibility, whereby most enhancers activate all promoters by similar amounts, and intrinsic enhancer and promoter activities multiplicatively combine to determine RNA output (R2 = 0.82). In addition, two classes of enhancers and promoters show subtle preferential effects. Promoters of housekeeping genes contain built-in activating motifs for factors such as GABPA and YY1, which decrease the responsiveness of promoters to distal enhancers. Promoters of variably expressed genes lack these motifs and show stronger responsiveness to enhancers. Together, this systematic assessment of enhancer-promoter compatibility suggests a multiplicative model tuned by enhancer and promoter class to control gene transcription in the human genome.


Assuntos
Elementos Facilitadores Genéticos , Regiões Promotoras Genéticas , Elementos Facilitadores Genéticos/genética , Humanos , Regiões Promotoras Genéticas/genética , RNA/biossíntese , RNA/genética , Fatores de Transcrição/metabolismo
3.
Nature ; 593(7858): 238-243, 2021 05.
Artigo em Inglês | MEDLINE | ID: mdl-33828297

RESUMO

Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complex traits, each of which could reveal insights into the mechanisms of disease1. Many of the underlying causal variants may affect enhancers2,3, but we lack accurate maps of enhancers and their target genes to interpret such variants. We recently developed the activity-by-contact (ABC) model to predict which enhancers regulate which genes and validated the model using CRISPR perturbations in several cell types4. Here we apply this ABC model to create enhancer-gene maps in 131 human cell types and tissues, and use these maps to interpret the functions of GWAS variants. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577 genes that appear to influence multiple phenotypes through variants in enhancers that act in different cell types. In inflammatory bowel disease (IBD), causal variants are enriched in predicted enhancers by more than 20-fold in particular cell types such as dendritic cells, and ABC achieves higher precision than other regulatory methods at connecting noncoding variants to target genes. These variant-to-function maps reveal an enhancer that contains an IBD risk variant and that regulates the expression of PPIF to alter the membrane potential of mitochondria in macrophages. Our study reveals principles of genome regulation, identifies genes that affect IBD and provides a resource and generalizable strategy to connect risk variants of common diseases to their molecular and cellular functions.


Assuntos
Elementos Facilitadores Genéticos/genética , Predisposição Genética para Doença , Variação Genética/genética , Genoma Humano/genética , Estudo de Associação Genômica Ampla , Doenças Inflamatórias Intestinais/genética , Linhagem Celular , Cromossomos Humanos Par 10/genética , Ciclofilinas/genética , Células Dendríticas , Feminino , Humanos , Macrófagos/metabolismo , Masculino , Mitocôndrias/metabolismo , Especificidade de Órgãos/genética , Fenótipo
4.
Comput Vis ECCV ; 12363: 103-120, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-33345257

RESUMO

For large-scale vision tasks in biomedical images, the labeled data is often limited to train effective deep models. Active learning is a common solution, where a query suggestion method selects representative unlabeled samples for annotation, and the new labels are used to improve the base model. However, most query suggestion models optimize their learnable parameters only on the limited labeled data and consequently become less effective for the more challenging unlabeled data. To tackle this, we propose a two-stream active query suggestion approach. In addition to the supervised feature extractor, we introduce an unsupervised one optimized on all raw images to capture diverse image features, which can later be improved by fine-tuning on new labels. As a use case, we build an end-to-end active learning framework with our query suggestion method for 3D synapse detection and mitochondria segmentation in connectomics. With the framework, we curate, to our best knowledge, the largest connectomics dataset with dense synapses and mitochondria annotation. On this new dataset, our method outperforms previous state-of-the-art methods by 3.1% for synapse and 3.8% for mitochondria in terms of region-of-interest proposal accuracy. We also apply our method to image classification, where it outperforms previous approaches on CIFAR-10 under the same limited annotation budget. The project page is https://zudi-lin.github.io/projects/#two_stream_active.

5.
Nat Genet ; 51(12): 1664-1669, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-31784727

RESUMO

Enhancer elements in the human genome control how genes are expressed in specific cell types and harbor thousands of genetic variants that influence risk for common diseases1-4. Yet, we still do not know how enhancers regulate specific genes, and we lack general rules to predict enhancer-gene connections across cell types5,6. We developed an experimental approach, CRISPRi-FlowFISH, to perturb enhancers in the genome, and we applied it to test >3,500 potential enhancer-gene connections for 30 genes. We found that a simple activity-by-contact model substantially outperformed previous methods at predicting the complex connections in our CRISPR dataset. This activity-by-contact model allows us to construct genome-wide maps of enhancer-gene connections in a given cell type, on the basis of chromatin state measurements. Together, CRISPRi-FlowFISH and the activity-by-contact model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.


Assuntos
Repetições Palindrômicas Curtas Agrupadas e Regularmente Espaçadas , Elementos Facilitadores Genéticos , Regiões Promotoras Genéticas , Animais , Fator de Transcrição GATA1/genética , Regulação da Expressão Gênica , Desacetilase 6 de Histona/genética , Humanos , Hibridização in Situ Fluorescente , Células K562 , Camundongos , Modelos Genéticos , RNA Guia
6.
Cell Rep ; 29(9): 2849-2861.e6, 2019 11 26.
Artigo em Inglês | MEDLINE | ID: mdl-31775050

RESUMO

During postnatal development, cerebellar climbing fibers alter their innervation strengths onto supernumerary Purkinje cell targets, generating a one-to-few connectivity pattern in adulthood. To get insight about the processes responsible for this remapping, we reconstructed serial electron microscopy datasets from mice during the first postnatal week. Between days 3 and 7, individual climbing fibers selectively add many synapses onto a subset of Purkinje targets in a positive-feedback manner, without pruning synapses from other targets. Active zone sizes of synapses associated with powerful versus weak inputs are indistinguishable. Changes in synapse number are thus the predominant form of early developmental plasticity. Finally, the numbers of climbing fibers and Purkinje cells in a local region nearly match. Initial over-innervation of Purkinje cells by climbing fibers is therefore economical: the number of axons entering a region is enough to assure that each ultimately retains a postsynaptic target and that none branched there in vain.


Assuntos
Cerebelo/fisiopatologia , Fibras Nervosas/metabolismo , Sinapses/metabolismo , Animais , Humanos , Camundongos
7.
Front Cell Dev Biol ; 7: 232, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31681765

RESUMO

The steady-state localization of Golgi-resident glycosylation enzymes in the Golgi apparatus depends on a balance between anterograde and retrograde transport. Using the Retention Using Selective Hooks (RUSH) assay and high-content screening, we identified small molecules that perturb the localization of Mannosidase II (ManII) used as a model cargo for Golgi resident enzymes. In particular, we found that two compounds known as EGFR tyrosine kinase inhibitors, namely BML-265 and Tyrphostin AG1478 disrupt Golgi integrity and abolish secretory protein transport of diverse cargos, thus inducing brefeldin A-like effects. Interestingly, BML-265 and Tyrphostin AG1478 affect Golgi integrity and transport in human cells but not in rodent cells. The effects of BML-265 are reversible since Golgi integrity and protein transport are quickly restored upon washout of the compounds. BML-265 and Tyrphostin AG1478 do not lead to endosomal tubulation suggesting that, contrary to brefeldin A, they do not target the trans-Golgi ARF GEF BIG1 and BIG2. They quickly induce COPI dissociation from Golgi membranes suggesting that, in addition to EGFR kinase, the cis-Golgi ARF GEF GBF1 might also be a target of these molecules. Accordingly, overexpression of GBF1 prevents the effects of BML-265 and Tyrphostin AG1478 on Golgi integrity.

8.
Cell ; 162(3): 648-61, 2015 Jul 30.
Artigo em Inglês | MEDLINE | ID: mdl-26232230

RESUMO

We describe automated technologies to probe the structure of neural tissue at nanometer resolution and use them to generate a saturated reconstruction of a sub-volume of mouse neocortex in which all cellular objects (axons, dendrites, and glia) and many sub-cellular components (synapses, synaptic vesicles, spines, spine apparati, postsynaptic densities, and mitochondria) are rendered and itemized in a database. We explore these data to study physical properties of brain tissue. For example, by tracing the trajectories of all excitatory axons and noting their juxtapositions, both synaptic and non-synaptic, with every dendritic spine we refute the idea that physical proximity is sufficient to predict synaptic connectivity (the so-called Peters' rule). This online minable database provides general access to the intrinsic complexity of the neocortex and enables further data-driven inquiries.


Assuntos
Microscopia Eletrônica de Varredura/métodos , Microtomia/métodos , Neocórtex/ultraestrutura , Neurônios/ultraestrutura , Animais , Automação , Axônios/ultraestrutura , Dendritos/ultraestrutura , Camundongos , Neocórtex/citologia , Sinapses/ultraestrutura , Vesículas Sinápticas/ultraestrutura
9.
Med Image Anal ; 22(1): 77-88, 2015 May.
Artigo em Inglês | MEDLINE | ID: mdl-25791436

RESUMO

Automated sample preparation and electron microscopy enables acquisition of very large image data sets. These technical advances are of special importance to the field of neuroanatomy, as 3D reconstructions of neuronal processes at the nm scale can provide new insight into the fine grained structure of the brain. Segmentation of large-scale electron microscopy data is the main bottleneck in the analysis of these data sets. In this paper we present a pipeline that provides state-of-the art reconstruction performance while scaling to data sets in the GB-TB range. First, we train a random forest classifier on interactive sparse user annotations. The classifier output is combined with an anisotropic smoothing prior in a Conditional Random Field framework to generate multiple segmentation hypotheses per image. These segmentations are then combined into geometrically consistent 3D objects by segmentation fusion. We provide qualitative and quantitative evaluation of the automatic segmentation and demonstrate large-scale 3D reconstructions of neuronal processes from a 27,000 µm(3) volume of brain tissue over a cube of 30 µm in each dimension corresponding to 1000 consecutive image sections. We also introduce Mojo, a proofreading tool including semi-automated correction of merge errors based on sparse user scribbles.


Assuntos
Encéfalo/ultraestrutura , Interpretação de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Microscopia Eletrônica/métodos , Neurônios/ultraestrutura , Reconhecimento Automatizado de Padrão/métodos , Algoritmos , Aumento da Imagem/métodos , Aprendizado de Máquina , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Técnica de Subtração
10.
Carcinogenesis ; 35(3): 670-82, 2014 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-24148822

RESUMO

RNA interference has boosted the field of functional genomics, by making it possible to carry out 'loss-of-function' screens in cultured cells. Here, we performed a small interfering RNA screening, in three breast cancer cell lines, for 101 candidate driver genes overexpressed in amplified breast tumors and belonging to eight amplicons on chromosomes 8q and 17q, investigating their role in cell survival/proliferation. This screening identified eight driver genes that were amplified, overexpressed and critical for breast tumor cell proliferation or survival. They included the well-described oncogenic driver genes for the 17q12 amplicon, ERBB2 and GRB7. Four of six other candidate driver genes-RAD21 and EIF3H, both on chromosome 8q23, CHRAC1 on chromosome 8q24.3 and TANC2 on chromosome 17q23-were confirmed to be driver genes regulating the proliferation/survival of clonogenic breast cancer cells presenting an amplification of the corresponding region. Indeed, knockdown of the expression of these genes decreased cell viability, through both cell cycle arrest and apoptosis induction, and inhibited the formation of colonies in anchorage-independent conditions, in soft agar. Strategies for inhibiting the expression of these genes or the function of the proteins they encode are therefore of potential value for the treatment of breast cancers presenting amplifications of the corresponding genomic region.


Assuntos
Neoplasias da Mama/genética , Divisão Celular/genética , Sobrevivência Celular/genética , Transformação Celular Neoplásica/genética , Cromossomos Humanos Par 17 , Cromossomos Humanos Par 8 , RNA Interferente Pequeno/genética , Sequência de Bases , Neoplasias da Mama/patologia , Proteínas de Ciclo Celular , Primers do DNA , Proteínas de Ligação a DNA/genética , Feminino , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Proteínas Nucleares/genética , Nucleoproteínas/genética , Fosfoproteínas/genética , Proteínas/genética , Reação em Cadeia da Polimerase em Tempo Real , Reação em Cadeia da Polimerase Via Transcriptase Reversa
11.
J Biomol Screen ; 18(10): 1321-9, 2013 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-24045582

RESUMO

Quantitative microscopy has proven a versatile and powerful phenotypic screening technique. Recently, image-based profiling has shown promise as a means for broadly characterizing molecules' effects on cells in several drug-discovery applications, including target-agnostic screening and predicting a compound's mechanism of action (MOA). Several profiling methods have been proposed, but little is known about their comparative performance, impeding the wider adoption and further development of image-based profiling. We compared these methods by applying them to a widely applicable assay of cultured cells and measuring the ability of each method to predict the MOA of a compendium of drugs. A very simple method that is based on population means performed as well as methods designed to take advantage of the measurements of individual cells. This is surprising because many treatments induced a heterogeneous phenotypic response across the cell population in each sample. Another simple method, which performs factor analysis on the cellular measurements before averaging them, provided substantial improvement and was able to predict MOA correctly for 94% of the treatments in our ground-truth set. To facilitate the ready application and future development of image-based phenotypic profiling methods, we provide our complete ground-truth and test data sets, as well as open-source implementations of the various methods in a common software framework.


Assuntos
Forma Celular/efeitos dos fármacos , Avaliação Pré-Clínica de Medicamentos/métodos , Análise Fatorial , Humanos , Células MCF-7 , Microscopia de Fluorescência , Fenótipo , Bibliotecas de Moléculas Pequenas , Máquina de Vetores de Suporte
12.
BMC Bioinformatics ; 12: 407, 2011 Oct 21.
Artigo em Inglês | MEDLINE | ID: mdl-22017789

RESUMO

BACKGROUND: Accurate quantitative co-localization is a key parameter in the context of understanding the spatial co-ordination of molecules and therefore their function in cells. Existing co-localization algorithms consider either the presence of co-occurring pixels or correlations of intensity in regions of interest. Depending on the image source, and the algorithm selected, the co-localization coefficients determined can be highly variable, and often inaccurate. Furthermore, this choice of whether co-occurrence or correlation is the best approach for quantifying co-localization remains controversial. RESULTS: We have developed a novel algorithm to quantify co-localization that improves on and addresses the major shortcomings of existing co-localization measures. This algorithm uses a non-parametric ranking of pixel intensities in each channel, and the difference in ranks of co-localizing pixel positions in the two channels is used to weight the coefficient. This weighting is applied to co-occurring pixels thereby efficiently combining both co-occurrence and correlation. Tests with synthetic data sets show that the algorithm is sensitive to both co-occurrence and correlation at varying levels of intensity. Analysis of biological data sets demonstrate that this new algorithm offers high sensitivity, and that it is capable of detecting subtle changes in co-localization, exemplified by studies on a well characterized cargo protein that moves through the secretory pathway of cells. CONCLUSIONS: This algorithm provides a novel way to efficiently combine co-occurrence and correlation components in biological images, thereby generating an accurate measure of co-localization. This approach of rank weighting of intensities also eliminates the need for manual thresholding of the image, which is often a cause of error in co-localization quantification. We envisage that this tool will facilitate the quantitative analysis of a wide range of biological data sets, including high resolution confocal images, live cell time-lapse recordings, and high-throughput screening data sets.


Assuntos
Algoritmos , Microscopia/métodos , Chaperonina 60/análise , Células HeLa , Humanos , Mitocôndrias/química , Sensibilidade e Especificidade
13.
Bioinformatics ; 27(8): 1179-80, 2011 Apr 15.
Artigo em Inglês | MEDLINE | ID: mdl-21349861

RESUMO

UNLABELLED: There is a strong and growing need in the biology research community for accurate, automated image analysis. Here, we describe CellProfiler 2.0, which has been engineered to meet the needs of its growing user base. It is more robust and user friendly, with new algorithms and features to facilitate high-throughput work. ImageJ plugins can now be run within a CellProfiler pipeline. AVAILABILITY AND IMPLEMENTATION: CellProfiler 2.0 is free and open source, available at http://www.cellprofiler.org under the GPL v. 2 license. It is available as a packaged application for Macintosh OS X and Microsoft Windows and can be compiled for Linux. CONTACT: anne@broadinstitute.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Processamento de Imagem Assistida por Computador/métodos , Software , Algoritmos , Ensaios de Triagem em Larga Escala , Neurônios/ultraestrutura
14.
Genome Res ; 21(3): 433-46, 2011 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-21239477

RESUMO

The evolutionarily conserved target of rapamycin complex 1 (TORC1) controls cell growth in response to nutrient availability and growth factors. TORC1 signaling is hyperactive in cancer, and regulators of TORC1 signaling may represent therapeutic targets for human diseases. To identify novel regulators of TORC1 signaling, we performed a genome-scale RNA interference screen on microarrays of Drosophila melanogaster cells expressing human RPS6, a TORC1 effector whose phosphorylated form we detected by immunofluorescence. Our screen revealed that the TORC1-S6K-RPS6 signaling axis is regulated by many subcellular components, including the Class I vesicle coat (COPI), the spliceosome, the proteasome, the nuclear pore, and the translation initiation machinery. Using additional RNAi reagents, we confirmed 70 novel genes as significant on-target regulators of RPS6 phosphorylation, and we characterized them with extensive secondary assays probing various arms of the TORC1 pathways, identifying functional relationships among those genes. We conclude that cell-based microarrays are a useful platform for genome-scale and secondary screening in Drosophila, revealing regulators that may represent drug targets for cancers and other diseases of deregulated TORC1 signaling.


Assuntos
Proteínas Recombinantes/metabolismo , Proteína S6 Ribossômica/metabolismo , Fatores de Transcrição/metabolismo , Animais , Western Blotting , Células Cultivadas , Proteínas de Drosophila/genética , Proteínas de Drosophila/metabolismo , Drosophila melanogaster/genética , Drosophila melanogaster/metabolismo , Imunofluorescência , Redes Reguladoras de Genes , Genoma , Genômica , Humanos , Análise em Microsséries , Terapia de Alvo Molecular , Fosforilação , Interferência de RNA , Proteínas Recombinantes/genética , Proteína S6 Ribossômica/genética , Transdução de Sinais/genética , Fatores de Transcrição/genética
15.
Nat Chem Biol ; 6(6): 457-63, 2010 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-20436488

RESUMO

We report the discovery of small molecules that target the Rho pathway, which is a central regulator of cytokinesis--the final step in cell division. We have developed a way of targeting a small molecule screen toward a specific pathway, which should be widely applicable to the investigation of any signaling pathway. In a chemical genetic variant of a classical modifier screen, we used RNA interference (RNAi) to sensitize cells and identified small molecules that suppressed or enhanced the RNAi phenotype. We discovered promising candidate molecules, which we named Rhodblock, and we identified the target of Rhodblock as Rho kinase. Several Rhodblocks inhibited one function of the Rho pathway in cells: the correct localization of phosphorylated myosin light chain during cytokinesis. Rhodblocks differentially perturb Rho pathway proteins in cells and can be used to dissect the mechanism of the Rho pathway during cytokinesis.


Assuntos
Citocinese/fisiologia , Quinases Associadas a rho/metabolismo , Animais , Citocinese/efeitos dos fármacos , Drosophila/enzimologia , Drosophila/genética , Drosophila/fisiologia , Proteínas de Drosophila/metabolismo , Inibidores Enzimáticos/farmacologia , GTP Fosfo-Hidrolases/metabolismo , Proteínas Ativadoras de GTPase/metabolismo , Guanosina Difosfato/metabolismo , Guanosina Trifosfato/metabolismo , Humanos , Aumento da Imagem , Cinética , Miosina Tipo II/metabolismo , Proteínas Proto-Oncogênicas/metabolismo , RNA/antagonistas & inibidores , RNA Mensageiro/efeitos dos fármacos , RNA Mensageiro/metabolismo , Transdução de Sinais , Quinases Associadas a rho/antagonistas & inibidores , Quinases Associadas a rho/efeitos dos fármacos
16.
Proc Natl Acad Sci U S A ; 106(6): 1826-31, 2009 Feb 10.
Artigo em Inglês | MEDLINE | ID: mdl-19188593

RESUMO

Many biological pathways were first uncovered by identifying mutants with visible phenotypes and by scoring every sample in a screen via tedious and subjective visual inspection. Now, automated image analysis can effectively score many phenotypes. In practical application, customizing an image-analysis algorithm or finding a sufficient number of example cells to train a machine learning algorithm can be infeasible, particularly when positive control samples are not available and the phenotype of interest is rare. Here we present a supervised machine learning approach that uses iterative feedback to readily score multiple subtle and complex morphological phenotypes in high-throughput, image-based screens. First, automated cytological profiling extracts hundreds of numerical descriptors for every cell in every image. Next, the researcher generates a rule (i.e., classifier) to recognize cells with a phenotype of interest during a short, interactive training session using iterative feedback. Finally, all of the cells in the experiment are automatically classified and each sample is scored based on the presence of cells displaying the phenotype. By using this approach, we successfully scored images in RNA interference screens in 2 organisms for the prevalence of 15 diverse cellular morphologies, some of which were previously intractable.


Assuntos
Algoritmos , Inteligência Artificial , Células , Citometria por Imagem/métodos , Interpretação de Imagem Assistida por Computador/métodos , Animais , Células/química , Células/citologia , Células/ultraestrutura , Diagnóstico por Imagem/métodos , Retroalimentação , Humanos , Reconhecimento Automatizado de Padrão/métodos , Fenótipo , Interferência de RNA , Análise Serial de Tecidos
17.
BMC Bioinformatics ; 9: 482, 2008 Nov 15.
Artigo em Inglês | MEDLINE | ID: mdl-19014601

RESUMO

BACKGROUND: Image-based screens can produce hundreds of measured features for each of hundreds of millions of individual cells in a single experiment. RESULTS: Here, we describe CellProfiler Analyst, open-source software for the interactive exploration and analysis of multidimensional data, particularly data from high-throughput, image-based experiments. CONCLUSION: The system enables interactive data exploration for image-based screens and automated scoring of complex phenotypes that require combinations of multiple measured features per cell.


Assuntos
Células/ultraestrutura , Biologia Computacional/métodos , Processamento de Imagem Assistida por Computador/métodos , Fenótipo , Software , Inteligência Artificial
18.
Genome Biol ; 7(10): R100, 2006.
Artigo em Inglês | MEDLINE | ID: mdl-17076895

RESUMO

Biologists can now prepare and image thousands of samples per day using automation, enabling chemical screens and functional genomics (for example, using RNA interference). Here we describe the first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler. CellProfiler can address a variety of biological questions quantitatively, including standard assays (for example, cell count, size, per-cell protein levels) and complex morphological assays (for example, cell/organelle shape or subcellular patterns of DNA or protein staining).


Assuntos
Perfilação da Expressão Gênica , Mutação , Relação Dose-Resposta a Droga , Processamento de Imagem Assistida por Computador , Modelos Genéticos , Fenótipo , Reprodutibilidade dos Testes , Software
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