922 resultados para High-Throughput Nucleotide Sequencing
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Background: Light microscopic analysis of diatom frustules is widely used both in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleo-environmental studies. In these applications, usually large numbers of frustules need to be identified and / or measured. Although there is a need for automation in these applications, and image processing and analysis methods supporting these tasks have previously been developed, they did not become widespread in diatom analysis. While methodological reports for a wide variety of methods for image segmentation, diatom identification and feature extraction are available, no single implementation combining a subset of these into a readily applicable workflow accessible to diatomists exists. Results: The newly developed tool SHERPA offers a versatile image processing workflow focused on the identification and measurement of object outlines, handling all steps from image segmentation over object identification to feature extraction, and providing interactive functions for reviewing and revising results. Special attention was given to ease of use, applicability to a broad range of data and problems, and supporting high throughput analyses with minimal manual intervention. Conclusions: Tested with several diatom datasets from different sources and of various compositions, SHERPA proved its ability to successfully analyze large amounts of diatom micrographs depicting a broad range of species. SHERPA is unique in combining the following features: application of multiple segmentation methods and selection of the one giving the best result for each individual object; identification of shapes of interest based on outline matching against a template library; quality scoring and ranking of resulting outlines supporting quick quality checking; extraction of a wide range of outline shape descriptors widely used in diatom studies and elsewhere; minimizing the need for, but enabling manual quality control and corrections. Although primarily developed for analyzing images of diatom valves originating from automated microscopy, SHERPA can also be useful for other object detection, segmentation and outline-based identification problems.
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Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.
The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.
The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.
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Transcription factors (TFs) control the temporal and spatial expression of target genes by interacting with DNA in a sequence-specific manner. Recent advances in high throughput experiments that measure TF-DNA interactions in vitro and in vivo have facilitated the identification of DNA binding sites for thousands of TFs. However, it remains unclear how each individual TF achieves its specificity, especially in the case of paralogous TFs that recognize distinct target genomic sites despite sharing very similar DNA binding motifs. In my work, I used a combination of high throughput in vitro protein-DNA binding assays and machine-learning algorithms to characterize and model the binding specificity of 11 paralogous TFs from 4 distinct structural families. My work proves that even very closely related paralogous TFs, with indistinguishable DNA binding motifs, oftentimes exhibit differential binding specificity for their genomic target sites, especially for sites with moderate binding affinity. Importantly, the differences I identify in vitro and through computational modeling help explain, at least in part, the differential in vivo genomic targeting by paralogous TFs. Future work will focus on in vivo factors that might also be important for specificity differences between paralogous TFs, such as DNA methylation, interactions with protein cofactors, or the chromatin environment. In this larger context, my work emphasizes the importance of intrinsic DNA binding specificity in targeting of paralogous TFs to the genome.
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Immunity is broadly defined as a mechanism of protection against non-self entities, a process which must be sufficiently robust to both eliminate the initial foreign body and then be maintained over the life of the host. Life-long immunity is impossible without the development of immunological memory, of which a central component is the cellular immune system, or T cells. Cellular immunity hinges upon a naïve T cell pool of sufficient size and breadth to enable Darwinian selection of clones responsive to foreign antigens during an initial encounter. Further, the generation and maintenance of memory T cells is required for rapid clearance responses against repeated insult, and so this small memory pool must be actively maintained by pro-survival cytokine signals over the life of the host.
T cell development, function, and maintenance are regulated on a number of molecular levels through complex regulatory networks. Recently, small non-coding RNAs, miRNAs, have been observed to have profound impacts on diverse aspects of T cell biology by impeding the translation of RNA transcripts to protein. While many miRNAs have been described that alter T cell development or functional differentiation, little is known regarding the role that miRNAs have in T cell maintenance in the periphery at homeostasis.
In Chapter 3 of this dissertation, tools to study miRNA biology and function were developed. First, to understand the effect that miRNA overexpression had on T cell responses, a novel overexpression system was developed to enhance the processing efficiency and ultimate expression of a given miRNA by placing it within an alternative miRNA backbone. Next, a conditional knockout mouse system was devised to specifically delete miR-191 in a cell population expressing recombinase. This strategy was expanded to permit the selective deletion of single miRNAs from within a cluster to discern the effects of specific miRNAs that were previously inaccessible in isolation. Last, to enable the identification of potentially therapeutically viable miRNA function and/or expression modulators, a high-throughput flow cytometry-based screening system utilizing miRNA activity reporters was tested and validated. Thus, several novel and useful tools were developed to assist in the studies described in Chapter 4 and in future miRNA studies.
In Chapter 4 of this dissertation, the role of miR-191 in T cell biology was evaluated. Using tools developed in Chapter 3, miR-191 was observed to be critical for T cell survival following activation-induced cell death, while proliferation was unaffected by alterations in miR-191 expression. Loss of miR-191 led to significant decreases in the numbers of CD4+ and CD8+ T cells in the periphery lymph nodes, but this loss had no impact on the homeostatic activation of either CD4+ or CD8+ cells. These peripheral changes were not caused by gross defects in thymic development, but rather impaired STAT5 phosphorylation downstream of pro-survival cytokine signals. miR-191 does not specifically inhibit STAT5, but rather directly targets the scaffolding protein, IRS1, which in turn alters cytokine-dependent signaling. The defect in peripheral T cell maintenance was exacerbated by the presence of a Bcl-2YFP transgene, which led to even greater peripheral T cell losses in addition to developmental defects. These studies collectively demonstrate that miR-191 controls peripheral T cell maintenance by modulating homeostatic cytokine signaling through the regulation of IRS1 expression and downstream STAT5 phosphorylation.
The studies described in this dissertation collectively demonstrate that miR-191 has a profound role in the maintenance of T cells at homeostasis in the periphery. Importantly, the manipulation of miR-191 altered immune homeostasis without leading to severe immunodeficiency or autoimmunity. As much data exists on the causative agents disrupting active immune responses and the formation of immunological memory, the basic processes underlying the continued maintenance of a functioning immune system must be fully characterized to facilitate the development of methods for promoting healthy immune function throughout the life of the individual. These findings also have powerful implications for the ability of patients with modest perturbations in T cell homeostasis to effectively fight disease and respond to vaccination and may provide valuable targets for therapeutic intervention.
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The two potato cyst nematode species, Globodera pallida and G. rostochiensis, are among the most important pests of potato. PCN are difficult to manage, while the two species respond differently to the main control methods. An increase in the incidence of G. pallida had been reported and is generally attributed to greater effectiveness of control measures against G. rostochiensis. The status of PCN in Ireland was studied using PCR. The results demonstrated qPCR to be an efficient means of high-throughput PCN sampling, being able to accurately identify both species in mixed-species populations. Species discrimination using qPCR revealed an increase in the incidence of G. pallida in Ireland in the absence of G. pallida-selective control measures. The population dynamics of G. pallida and G. rostochiensis in Ireland were studied in mixed- and single-species competition assays in vivo. G. pallida proved to be the more successful species, with greater multiplication in mixed- than single-species populations, with G. rostochiensis showing the opposite. This effect was similarly observed in staggered inoculation trials and population proportion trials. It was hypothesised that the greater G. pallida competitiveness could be attributed to its later hatch. G. pallida exhibited a later peak in hatching activity and more prolonged hatch, relative to G. rostochiensis. G. rostochiensis hatch was significantly reduced in mixedspecies hatching assays. G. pallida hatch was significantly higher when hatch was induced in potato root leachates containing G. rostochiensis-specific compounds, indicating that G. pallida hatch is stimulated upon perception of G. rostochiensis–derived compounds. Rhizotron studies revealed that root damage, caused by feeding of the early-hatching G. rostochiensis, resulted in increased lateral root proliferation and significantly increased G. pallida multiplication. Split-root trials indicated a significant G. pallida-induced ISR effect. G. rostochiensis multiplication was significantly reduced in split-root rhizotrons when G. pallida colonised roots before or after G. rostochiensis infection.
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Major food adulteration and contamination events occur with alarming regularity and are known to be episodic, with the question being not if but when another large-scale food safety/integrity incident will occur. Indeed, the challenges of maintaining food security are now internationally recognised. The ever increasing scale and complexity of food supply networks can lead to them becoming significantly more vulnerable to fraud and contamination, and potentially dysfunctional. This can make the task of deciding which analytical methods are more suitable to collect and analyse (bio)chemical data within complex food supply chains, at targeted points of vulnerability, that much more challenging. It is evident that those working within and associated with the food industry are seeking rapid, user-friendly methods to detect food fraud and contamination, and rapid/high-throughput screening methods for the analysis of food in general. In addition to being robust and reproducible, these methods should be portable and ideally handheld and/or remote sensor devices, that can be taken to or be positioned on/at-line at points of vulnerability along complex food supply networks and require a minimum amount of background training to acquire information rich data rapidly (ergo point-and-shoot). Here we briefly discuss a range of spectrometry and spectroscopy based approaches, many of which are commercially available, as well as other methods currently under development. We discuss a future perspective of how this range of detection methods in the growing sensor portfolio, along with developments in computational and information sciences such as predictive computing and the Internet of Things, will together form systems- and technology-based approaches that significantly reduce the areas of vulnerability to food crime within food supply chains. As food fraud is a problem of systems and therefore requires systems level solutions and thinking.
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Schistosomiasis, caused by blood flukes of the genus Schistosoma, is a major public health problem which contributes substantially to the economic and financial burdens of many nations in the developing world. An array of survival strategies, such as the unique structure of the tegument which acts as a major host-parasite interface, immune modulation mechanisms, gene regulation, and apoptosis and self-renewal have been adopted by schistosome parasites over the course of long-term evolution with their mammalian definitive hosts. Recent generation of complete schistosome genomes together with numerous biological, immunological, high-throughput "-omics" and gene function studies have revealed the Tao or strategies that schistosomes employ not only to promote long-term survival, but also to ensure effective life cycle transmission. New scenarios for the future control of this important neglected tropical disease will present themselves as our understanding of these Tao increases.
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New targeted approaches to ovarian clear cell carcinomas (OCCC) are needed, given the limited treatment options in this disease and the poor response to standard chemotherapy. Using a series of high-throughput cell-based drug screens in OCCC tumor cell models, we have identified a synthetic lethal (SL) interaction between the kinase inhibitor dasatinib and a key driver in OCCC, ARID1A mutation. Imposing ARID1A deficiency upon a variety of human or mouse cells induced dasatinib sensitivity, both in vitro and in vivo, suggesting that this is a robust synthetic lethal interaction. The sensitivity of ARID1A-deficient cells to dasatinib was associated with G1 -S cell-cycle arrest and was dependent upon both p21 and Rb. Using focused siRNA screens and kinase profiling, we showed that ARID1A-mutant OCCC tumor cells are addicted to the dasatinib target YES1. This suggests that dasatinib merits investigation for the treatment of patients with ARID1Amutant OCCC. Mol Cancer Ther; 15(7); 1472-84. Ó2016 AACR.
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Repositories containing high quality human biospecimens linked with robust and relevant clinical and pathological information are required for the discovery and validation of biomarkers for disease diagnosis, progression and response to treatment. Current molecular based discovery projects using either low or high throughput technologies rely heavily on ready access to such sample collections. It is imperative that modern biobanks align with molecular diagnostic pathology practices not only to provide the type of samples needed for discovery projects but also to ensure requirements for ongoing sample collections and the future needs of researchers are adequately addressed. Biobanks within comprehensive molecular pathology programmes are perfectly positioned to offer more than just tumour derived biospecimens; for example, they have the ability to facilitate researchers gaining access to sample metadata such as digitised scans of tissue samples annotated prior to macrodissection for molecular diagnostics or pseudoanonymised clinical outcome data or research results retrieved from other users utilising the same or overlapping cohorts of samples. Furthermore, biobanks can work with molecular diagnostic laboratories to develop standardized methodologies for the acquisition and storage of samples required for new approaches to research such as ‘liquid biopsies’ which will ultimately feed into the test validations required in large prospective clinical studies in order to implement liquid biopsy approaches for routine clinical practice. We draw on our experience in Northern Ireland to discuss how this harmonised approach of biobanks working synergistically with molecular pathology programmes is key for the future success of precision medicine.
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Densification is a key to greater throughput in cellular networks. The full potential of coordinated multipoint (CoMP) can be realized by massive multiple-input multiple-output (MIMO) systems, where each base station (BS) has very many antennas. However, the improved throughput comes at the price of more infrastructure; hardware cost and circuit power consumption scale linearly/affinely with the number of antennas. In this paper, we show that one can make the circuit power increase with only the square root of the number of antennas by circuit-aware system design. To this end, we derive achievable user rates for a system model with hardware imperfections and show how the level of imperfections can be gradually increased while maintaining high throughput. The connection between this scaling law and the circuit power consumption is established for different circuits at the BS.
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Burkholderia phage AP3 (vB_BceM_AP3) is a temperate virus of the Myoviridae and the Peduovirinae subfamily (P2likevirus genus). This phage specifically infects multidrug-resistant clinical Burkholderia cenocepacia lineage IIIA strains commonly isolated from cystic fibrosis patients. AP3 exhibits high pairwise nucleotide identity (61.7%) to Burkholderia phage KS5, specific to the same B. cenocepacia host, and has 46.7% - 49.5% identity to phages infecting other species of Burkholderia. The lysis cassette of these related phages has a similar organization (putative antiholin, putative holin, endolysin and spanins) and shows 29-98% homology between specific lysis genes, in contrast to Enterobacteria phage P2, the hallmark phage of this genus. The AP3 and KS5 lysis genes have conserved locations and high amino acid sequence similarity. The AP3 bacteriophage particles remain infective up to 5 h at pH 4-10 and are stable at 60°C for 30 min, but are sensitive to chloroform, with no remaining infective particles after 24 h of treatment. AP3 lysogeny can occur by stable genomic integration and by pseudo-lysogeny. The lysogenic bacterial mutants did not exhibit any significant changes in virulence compared to wild-type host strain when tested in the Galleria mellonella moth wax model. Moreover, AP3 treatment of larvae infected with B. cenocepacia revealed a significant increase (P < 0.0001) in larvae survival in comparison to AP3-untreated infected larvae. AP3 showed robust lytic activity, as evidenced by its broad host range, the absence of increased virulence in lysogenic isolates, the lack of bacterial gene disruption conditioned by bacterial tRNA downstream integration site, and the absence of detected toxin sequences. These data suggest the AP3 phage is a promising potent agent against bacteria belonging to most common B. cenocepacia IIIA lineage strains.
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Genetic mutations can cause a wide range of diseases, e.g. cancer. Gene therapy has the potential to alleviate or even cure these diseases. One of the many gene therapies developed so far is RNA-cleaving deoxyribozymes, short DNA oligonucleotides that specifically bind to and cleave RNA. Since the development of these synthetic catalytic oligonucleotides, the main way of determining their cleavage kinetics has been through the use of a laborious and error prone gel assay to quantify substrate and product at different time-points. We have developed two new methods for this purpose. The first one includes a fluorescent intercalating dye, PicoGreen, which has an increased fluorescence upon binding double-stranded oligonucleotides; during the course of the reaction the fluorescence intensity will decrease as the RNA is cleaved and dissociates from the deoxyribozyme. A second method was developed based on the common denominator of all nucleases, each cleavage event exposes a single phosphate of the oligonucleotide phosphate backbone; the exposed phosphate can simultaneously be released by a phosphatase and directly quantified by a fluorescent phosphate sensor. This method allows for multiple turnover kinetics of diverse types of nucleases, including deoxyribozymes and protein nucleases. The main challenge of gene therapy is often the delivery into the cell. To bypass cellular defenses researchers have used a vast number of methods; one of these are cell-penetrating peptides which can be either covalently coupled to or non-covalently complexed with a cargo to deliver it into a cell. To further evolve cell-penetrating peptides and understand how they work we developed an assay to be able to quickly screen different conditions in a high-throughput manner. A luciferase up- and downregulation experiment was used together with a reduction of the experimental time by 1 day, upscaling from 24- to 96-well plates and the cost was reduced by 95% compared to commercially available assays. In the last paper we evaluated if cell-penetrating peptides could be used to improve the uptake of an LNA oligonucleotide mimic of GRN163L, a telomerase-inhibiting oligonucleotide. The combination of cell-penetrating peptides and our mimic oligonucleotide lead to an IC50 more than 20 times lower than that of GRN163L.
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In dieser Arbeit werden optische Filterarrays für hochqualitative spektroskopische Anwendungen im sichtbaren (VIS) Wellenlängenbereich untersucht. Die optischen Filter, bestehend aus Fabry-Pérot (FP)-Filtern für hochauflösende miniaturisierte optische Nanospektrometer, basieren auf zwei hochreflektierenden dielektrischen Spiegeln und einer zwischenliegenden Resonanzkavität aus Polymer. Jeder Filter erlaubt einem schmalbandigem spektralen Band (in dieser Arbeit Filterlinie genannt) ,abhängig von der Höhe der Resonanzkavität, zu passieren. Die Effizienz eines solchen optischen Filters hängt von der präzisen Herstellung der hochselektiven multispektralen Filterfelder von FP-Filtern mittels kostengünstigen und hochdurchsatz Methoden ab. Die Herstellung der multiplen Spektralfilter über den gesamten sichtbaren Bereich wird durch einen einzelnen Prägeschritt durch die 3D Nanoimprint-Technologie mit sehr hoher vertikaler Auflösung auf einem Substrat erreicht. Der Schlüssel für diese Prozessintegration ist die Herstellung von 3D Nanoimprint-Stempeln mit den gewünschten Feldern von Filterkavitäten. Die spektrale Sensitivität von diesen effizienten optischen Filtern hängt von der Genauigkeit der vertikalen variierenden Kavitäten ab, die durch eine großflächige ‚weiche„ Nanoimprint-Technologie, UV oberflächenkonforme Imprint Lithographie (UV-SCIL), ab. Die Hauptprobleme von UV-basierten SCIL-Prozessen, wie eine nichtuniforme Restschichtdicke und Schrumpfung des Polymers ergeben Grenzen in der potenziellen Anwendung dieser Technologie. Es ist sehr wichtig, dass die Restschichtdicke gering und uniform ist, damit die kritischen Dimensionen des funktionellen 3D Musters während des Plasmaätzens zur Entfernung der Restschichtdicke kontrolliert werden kann. Im Fall des Nanospektrometers variieren die Kavitäten zwischen den benachbarten FP-Filtern vertikal sodass sich das Volumen von jedem einzelnen Filter verändert , was zu einer Höhenänderung der Restschichtdicke unter jedem Filter führt. Das volumetrische Schrumpfen, das durch den Polymerisationsprozess hervorgerufen wird, beeinträchtigt die Größe und Dimension der gestempelten Polymerkavitäten. Das Verhalten des großflächigen UV-SCIL Prozesses wird durch die Verwendung von einem Design mit ausgeglichenen Volumen verbessert und die Prozessbedingungen werden optimiert. Das Stempeldesign mit ausgeglichen Volumen verteilt 64 vertikal variierenden Filterkavitäten in Einheiten von 4 Kavitäten, die ein gemeinsames Durchschnittsvolumen haben. Durch die Benutzung der ausgeglichenen Volumen werden einheitliche Restschichtdicken (110 nm) über alle Filterhöhen erhalten. Die quantitative Analyse der Polymerschrumpfung wird in iii lateraler und vertikaler Richtung der FP-Filter untersucht. Das Schrumpfen in vertikaler Richtung hat den größten Einfluss auf die spektrale Antwort der Filter und wird durch die Änderung der Belichtungszeit von 12% auf 4% reduziert. FP Filter die mittels des Volumengemittelten Stempels und des optimierten Imprintprozesses hergestellt wurden, zeigen eine hohe Qualität der spektralen Antwort mit linearer Abhängigkeit zwischen den Kavitätshöhen und der spektralen Position der zugehörigen Filterlinien.
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Oomycete diseases cause significant losses across a broad range of crop and aquaculture commodities worldwide. These losses can be greatly reduced by disease management practices steered by accurate and early diagnoses of pathogen presence. Determinations of disease potential can help guide optimal crop rotation regimes, varietal selections, targeted control measures, harvest timings and crop post-harvest handling. Pathogen detection prior to infection can also reduce the incidence of disease epidemics. Classical methods for the isolation of oomycete pathogens are normally deployed only after disease symptom appearance. These processes are often-time consuming, relying on culturing the putative pathogen(s) and the availability of expert taxonomic skills for accurate identification; a situation that frequently results in either delayed application, or routine ‘blanket’ over-application of control measures. Increasing concerns about pesticides in the environment and the food chain, removal or restriction of their usage combined with rising costs have focussed interest in the development and improvement of disease management systems. To be effective, these require timely, accurate and preferably quantitatve diagnoses. A wide range of rapid diagnostic tools, from point of care immunodiagnostic kits to next generation nucleotide sequencing have potential application in oomycete disease management. Here we review currently-available as well as promising new technologies in the context of commercial agricultural production systems, considering the impacts of specific biotic and abiotic and other important factors such as speed and ease of access to information and cost effectiveness
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Objective: The study was designed to validate use of elec-tronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects. Method: EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype di- agnoses was calculated against diagnoses from direct semi- structured interviews of 190 patients by trained clinicians blind to EHR diagnosis. Results: The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR- classified control subject received a diagnosis of bipolar dis- order on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based clas- sifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses. Conclusions: Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.