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The purpose of this Funding Opportunity Announcement (FOA) is to support a consortium of collaborative projects, with a minimum of two sites, that propose to use cutting edge technologies to generate and analyze whole genome sequencing (WGS) data from either case control or family samples in order to elucidate the full genetic architecture underlying susceptibility to severe mental disorders. Insights into the genetic architecture underlying susceptibility to severe mental disorders will be achieved through implementation of state of the art WGS assays and innovative/novel statistical methods.

The Communications, Circuits, and Sensing-Systems (CCSS) program is intended to spur visionary systems-oriented activities in collaborative, multidisciplinary, and integrative research. CCSS supports systems research in hardware, signal processing techniques, and architectures to enable the next generation of cyber-physical systems (CPS) that leverage computation, communication, and algorithms integrated with physical domains. CCSS offers new challenges at all levels of systems integration to address future societal needs. CCSS supports innovative research and integrated educational activities in micro- and nano-systems, communications systems, and cyber-physical systems. The goal is to design, develop, and implement new complex and hybrid systems at all scales, including nano, micro, and macro, that lead to innovative engineering principles and solutions for a variety of application domains including, but not limited to, healthcare, medicine, environmental monitoring, communications, disaster mitigation, homeland security, transportation, manufacturing, energy, and smart buildings. CCSS also supports integration technologies at both intra-and inter-chip levels, new and advanced radio frequency (RF), millimeter wave and optical wireless and hybrid communications systems architectures, and sensing and imaging at terahertz (THz) frequencies.

The Energy, Power, Control, and Networks (EPCN) Program supports innovative research in modeling, optimization, learning, adaptation, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation, as well as risk management in the presence of uncertainty, sub-system failures, and stochastic disturbances. EPCN also invests in novel machine learning algorithms and analysis, adaptive dynamic programming, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN's goal is to encourage research on emerging technologies and applications including energy, transportation, robotics, and biomedical devices & systems. EPCN also emphasizes electric power systems, including generation, transmission, storage, and integration of renewable energy sources into the grid; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory & economic structures and with consumer behavior.

This initiative will foster collaborative and coordinated efforts to characterize the underlying genetic architecture of diverse neuropsychiatric phenotypes within and across rare genetic disorders and identify the shared genetic risk across rare and idiopathic neuropsychiatric disorders. Projects from multi-disciplinary teams will utilize genome-wide data to comprehensively assess the contribution of genetic variation to the variable expressivity and incomplete penetrance of neuropsychiatric phenotypes across rare genetic disorders. Projects are encouraged to leverage existing resources, cohorts, and collaborative networks with established infrastructure for consistent and high-quality phenotypic data collection and genomic data generation. Projects should seek to enhance the quality of the phenotypic data available for rare genetic disorders by developing or applying phenotyping methodologies that create a pipeline for standardizing assessments and that cut across rare genetic disorders and across developmental time points. Under this initiative, investigators will form a network to facilitate data sharing and harmonization of clinical and genetic data across different studies within the network, as well as accelerate characterization of genotype to phenotype relationships across rare genetic disorders. This network will also generate a resource of bio-samples, as well as phenotypic and genetic data for broader dissemination to the scientific community. This FOA should be used for applications that are not collaborative between sites. Applications requiring two or more collaborating sites to complete the proposed research should apply as a linked set of collaborative U01 applications to the companion collaborative U01 FOA (RFA-MH-19-201). All awards supported under this FOA and the companion collaborative U01 FOA (RFA -MH-19-201) will be governed by the Mental Health Rare Genetic Disease Network (MHRGDN).

This initiative will foster collaborative and coordinated efforts to characterize the underlying genetic architecture of diverse neuropsychiatric phenotypes within and across rare genetic disorders and identify the shared genetic risk across rare and idiopathic neuropsychiatric disorders. Projects from multi-disciplinary teams will utilize genome-wide data to comprehensively assess the contribution of genetic variation to the variable expressivity and incomplete penetrance of neuropsychiatric phenotypes across rare genetic disorders. Projects are encouraged to leverage existing resources, cohorts, and collaborative networks with established infrastructure for consistent and high-quality phenotypic data collection and genomic data generation. Projects should seek to enhance the quality of the phenotypic data available for rare genetic disorders by developing or applying phenotyping methodologies that create a pipeline for standardizing assessments and that cut across rare genetic disorders and across developmental time points. Under this initiative, investigators will form a network to facilitate data sharing and harmonization of clinical and genetic data across different studies within the network, as well as accelerate characterization of genotype to phenotype relationships across rare genetic disorders. This network will also generate a resource of bio-samples, as well as phenotypic and genetic data for broader dissemination to the scientific community.

Epidemiological studies have shown that psychiatric disorders, constitute a significant public health burden across diverse populations worldwide. These mental disorders are characterized by marked genetic heterogeneity, with both common and rare variation contributing to the complex phenotypic outcomes. For reasons such as population homogeneity and ease of ascertainment, most genome-wide genetic studies to date have mainly focused on cohorts of European-ancestry, however, no single population is sufficient to fully uncover the variants underlying neuropsychiatric diseases in all populations. The absence of diverse ancestries in genome-wide association studies has therefore negatively impacted their ability to illuminate the full genetic architecture of complex neuropsychiatric traits. Populations with different ancestral origins vary in terms of allele frequencies, biological adaptations, and other properties that affect the detectability and importance of risk variants. Lack of ancestrally diverse genome-wide data can lead to the misidentification of causal variants due to cryptic population stratification or simply overlooking a causal variant altogether, since rare variants are likely to be more recent in origin and more geographically localized.

Through this Funding Opportunity Announcement (FOA), the National Institute of Mental Health (NIMH) seeks applications to develop, sustain, enhance, and enrich a centralized national biorepository for genetic studies of psychiatric disorders for facilitation and acceleration of the scientific understanding of the genetic risk architecture underlying mental disorders. This effort is expected to involve a functionally integrated, multi-disciplinary team that will provide for open sharing of biosamples and data resources through a single, centralized, national resource to advance basic and translational research in the genetics of mental disorders.

The U.S. Environmental Protection Agency (EPA), as part of its Science to Achieve Results (STAR) program, is seeking applications for research centers to investigate toxic effects of chemical substances in three-dimensional (3D) in vitro models, hereafter referred to as 'organotypic culture models' (OCMs). OCMs are tissue culture models that mimic in vivo tissue architecture through interactions of heterotypic cell types (e.g., epithelium-stroma) and extracellular matrices (ECM). They can be established from isolated cells or from tissue fragments harvested in vivo, and will bridge the gap between conventional monolayer cell cultures and whole-animal systems. EPA is interested in the potential application of OCMs that mimic complex cell arrangements and physiologies, scalable from mid to higher throughput screening (HTS), and high-content screening (HCS) approaches. This solicitation seeks the formation of research centers that will guide the development and evaluation of OCMs that will accelerate translational research in predictive toxicology. Three dimensional tissue models may, for example, utilize animal cells combined with mechanical scaffolds or microfluidics devices. Under this solicitation, the successful applicant will lead a Center to craft OCMs that can recapitulate critical features of in vivo cellular organization and communication, cell-matrix interplay, morphogenetic processes and differentiation, physiology and chemical metabolism. 

The purpose of this FOA is to support projects to develop tools and strategies for studying: 1. the three dimensional architecture of the nucleus in relationship to the topography of nuclear bodies and transcriptional machineries, 2. the structure and function of poorly characterized nuclear structures, or 3. the role of specialized proteins and RNAs in the assembly, organization, and function of nuclear bodies, nuclear structures, and specialized subnuclear domains. - See more at: http://grants.nih.gov/grants/guide/rfa-files/RFA-RM-14-008.html#sthash.HQemmZlU.dpuf

All of comparative biology depends on knowledge of the evolutionary relationships (phylogeny) of living and extinct organisms. In addition, understanding biodiversity and how it changes over time is only possible when Earth's diversity is organized into a phylogenetic framework. The goals of the Genealogy of Life (GoLife) program are to resolve the phylogenetic history of life and to integrate this genealogical architecture with underlying organismal data. The ultimate vision of this program is an open access, universal Genealogy of Life that will provide the comparative framework necessary for testing questions in systematics, evolutionary biology, ecology, and other fields. A further strategic integration of this genealogy of life with data layers from genomic, phenotypic, spatial, ecological and temporal data will produce a grand synthesis of biodiversity and evolutionary sciences. The resulting knowledge infrastructure will enable synthetic research on biological dynamics throughout the history of life on Earth, within current ecosystems, and for predictive modeling of the future evolution of life. Projects submitted to this program should emphasize increased efficiency in contributing to a complete Genealogy of Life and integration of various types of organismal data with phylogenies. This program also seeks to broadly train next generation, integrative phylogenetic biologists, creating the human resource infrastructure and workforce needed to tackle emerging research questions in comparative biology. Projects should train students for diverse careers by exposing them to the multidisciplinary areas of research within the proposal.

All of comparative biology depends on knowledge of the evolutionary relationships (phylogeny) of living and extinct organisms. In addition, understanding biodiversity and how it changes over time is only possible when Earth's diversity is organized into a phylogenetic framework. The goals of the Genealogy of Life (GoLife) program are to resolve the phylogenetic history of life and to integrate this genealogical architecture with underlying organismal data. The ultimate vision of this program is an open access, universal Genealogy of Life that will provide the comparative framework necessary for testing questions in systematics, evolutionary biology, ecology, and other fields. A further strategic integration of this genealogy of life with data layers from genomic, phenotypic, spatial, ecological and temporal data will produce a grand synthesis of biodiversity and evolutionary sciences. The resulting knowledge infrastructure will enable synthetic research on biological dynamics throughout the history of life on Earth, within current ecosystems, and for predictive modeling of the future evolution of life.Projects submitted to this program should emphasize increased efficiency in contributing to a complete Genealogy of Life and integration of various types of organismal data with phylogenies.This program also seeks to broadly train next generation, integrative phylogenetic biologists, creating the human resource infrastructure and workforce needed to tackle emerging research questions in comparative biology. Projects should train students for diverse careers by exposing them to the multidisciplinary areas of research within the proposal.

Comprehensive understanding of life and how and why it changes over time depends on knowledge of the phylogeny (evolutionary relationships) of living and extinct organisms. The goals of the Genealogy of Life (GoLife) program are to resolve the phylogenetic history of all life’s diverse forms and to integrate this genealogical architecture with underlying organismal and environmental data. The ultimate vision of this program is an open access, comprehensive Genealogy of Life that will provide the comparative framework necessary for testing questions in systematics, evolutionary biology, ecology, and other fields. Strategic integration of this genealogy of life with data layers from genomic, phenotypic, spatial, ecological and temporal data will produce an extensive synthesis of biodiversity and evolutionary sciences. The resulting knowledge infrastructure will enable synthetic research on biological dynamics throughout the history of life on Earth, within current ecosystems, and for predictive modeling of the future evolution of life. Projects submitted to this program should emphasize increased efficiency in contributing to a complete Genealogy of Life and strategic integration of various types of organismal and environmental data with phylogenies. This program also seeks to broadly train next generation, integrative phylogenetic biologists, creating the human resource infrastructure and workforce needed to tackle emerging research questions in comparative biology. Projects should train students for diverse careers by exposing them to the multidisciplinary areas of research within the proposal.

Comprehensive understanding of life and how and why it changes over time depends on knowledge of the phylogeny (evolutionary relationships) of living and extinct organisms. The goals of the Genealogy of Life (GoLife) program are to resolve the phylogenetic history of all life's diverse forms and to integrate this genealogical architecture with underlying organismal and environmental data.

The unique high quality and long duration microgravity environment on the ISS National Lab provides an extraordinary research platform for experiments in the biological and medical sciences. Microgravity induces a vast array of changes in individual cells and model organisms ranging from viruses and microorganisms to humans, including global alterations in gene expression and 3-dimensional aggregation of cells into biofilms or tissue-like architectures that recapitulate the structure and function of organs. Moreover, studies of astronauts reveal a variety of space flight-induced health conditions, many of which may serve as accelerated models of ground-based ailments such as aging and trauma. Research into these and other effects of the space environment may advance our fundamental understanding of cell and tissue function, effective disease diagnosis and /or treatment, or improved health care delivery.

This Funding Opportunity Announcement (FOA) invites cooperative agreement applications that will contribute to a higher resolution understanding of the physical and functional organization of the human islet tissue environment by describing the composition (cellular and molecular) and function of important components of the pancreatic islet and peri-islet tissue architecture, the cell-cell relationships and means of communications used by cell types and cell subtypes within the pancreatic tissue ecosystem, and/or the contribution of adjacent (including acinar, ductal, lymphatic) and neighboring (intestinal, mesenteric and adipose) tissues to islet cell function and dysfunction. Successful projects will integrate the Human Pancreas Analysis Consortium (HPAC), that will consist of the research teams funded in response to this FOA with the Human Pancreas Analysis Program (HPAP), a resource-generation program that was funded in 2016 in response to RFA-DK-15-027. HPAC will become the fifth consortium of the Human Islet Research Network (HIRN, https://hirnetwork.org/ ). HIRN's overall mission is to support innovative and collaborative translational research to understand how human beta cells are lost in T1D, and to find innovative strategies to protect and replace functional beta cell mass in humans. This FOA will only support studies with a primary focus on increasing our understanding of human tissue structure and function, and human disease biology (as opposed to rodent or other animal models). This FOA is not intended to support the conduct of a clinical trial.

This Funding Opportunity Announcement (FOA) invites cooperative agreement applications that will contribute to a higher resolution understanding of the physical and functional organization of the human islet tissue environment by describing the composition (cellular and molecular) and function of important components of the pancreatic islet and peri-islet tissue architecture, the cell-cell relationships and means of communications used by cell types and cell subtypes within the pancreatic tissue ecosystem, and/or the contribution of adjacent (including acinar, ductal, lymphatic) and neighboring (intestinal, mesenteric and adipose) tissues to islet cell function and dysfunction. Successful projects will integrate the Human Pancreas Analysis Consortium (HPAC), that will consist of the research teams funded in response to this FOA with the Human Pancreas Analysis Program (HPAP), a resource-generation program that was funded in 2016 in response to RFA-DK-15-027. HPAC will become the fifth consortium of the Human Islet Research Network (HIRN, https://hirnetwork.org/ ). HIRN's overall mission is to support innovative and collaborative translational research to understand how human beta cells are lost in T1D, and to find innovative strategies to protect and replace functional beta cell mass in humans. This FOA will only support studies with a primary focus on increasing our understanding of human tissue structure and function, and human disease biology (as opposed to rodent or other animal models). This FOA will not accept applications proposing a clinical trial.

This Funding Opportunity Announcement (FOA) encourages research grant applications directed toward developing next-generation human cell-derived assays that replicate complex nervous system architectures and physiology with improved fidelity over current capabilities. This includes technologies that do not rely on the use of human fetal tissue, as described in NOT-19-042. Supported projects will be expected to enable future studies of complex nervous system development, function and aging in healthy and disease states.

CIFAR invites exceptional early career researchers to join CIFAR's global network of 370 researchers from 18 countries who together are pursuing answers to some of the most complex challenges facing the world today. The CIFAR Azrieli Global Scholars program provides funding, skills training, mentorship, and opportunities to collaborate with outstanding colleagues from diverse disciplines to position scholars as leaders and agents of change within academia and beyond. CIFAR Azrieli Global Scholars receive: * $100,000 CDN in unrestricted research support * A two-year membership to a CIFAR research program, with outstanding research leaders from across disciplines. Learn what it's like to be a CIFAR Fellow * Specialized leadership and communication skills training Applicants can be from anywhere in the world, must hold a PhD (or equivalent) and be within the first five years of a full-time academic appointment. Please note that postdoctoral fellows are not eligible to apply to the program. Scholars' research interests must be aligned with the themes of an eligible CIFAR research program.  In 2018, the eligible programs are: * Azrieli Program in Brain, Mind & Consciousness * Bio-Inspired Solar Energy * Gravity & the Extreme Universe * Humans & the Microbiome * Molecular Architecture of Life

To support the development and application of tools that would enable the monitoring in real-time of the dynamic three-dimensional structure of mammalian genomes and provide insight into how organizing components of 4D genome architecture affect biological processes in live cells.

To support the development and application of tools that would enable the monitoring in real-time of the dynamic three-dimensional structure of mammalian genomes and provide insight into how organizing components of 4D genome architecture affect biological processes in live cells.