BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain (R01 Clinical Trial Not Allowed)

This funding opportunity announcement (FOA) encourages applications for institutional research career development (K12) programs that propose to support intensive supervised research training and career development experiences for clinician scientists (Scholars) leading to research independence in the area of substance use and substance use disorder research.

Through this Notice of Funding Opportunity, the National Cancer Institute (NCI) seeks research projects that implement early phase (Phase 0, I, and II) investigator-initiated clinical trials focused on cancer-targeted diagnostic and therapeutic interventions of direct relevance to the research mission of DCTD and OHAM. The proposed project must involve at least 1 clinical trial related to the scientific interests of one or more of the following research programs: Cancer Therapy Evaluation Program, Cancer Imaging Program, Cancer Diagnosis Program, Radiation Research Program, Complementary and Alternative Medicine Program and/or the HIV and AIDS Malignancies Research Programs. Applicants may propose to conduct an early phase trial by itself, or in combination with another research aim(s) as appropriate.

Through this Notice of Funding Opportunity (NOFO), the National Cancer Institute (NCI) along with other participating Institutes encourages submission of applications proposing to conduct secondary data analysis and integration of existing datasets and database resources, with the ultimate aim to elucidate cancer risk and related outcomes (e.g., risk prediction or reduction, survival, or response to treatment, etc.). The goal of this initiative is to address key scientific questions relevant to cancer by supporting the analysis of existing clinical, environmental, surveillance, health services, vital statistics, behavioral, lifestyle, genomic, and molecular profiles data. Applicants are encouraged to leverage and perform innovative analyses of the existing data. Applications may include new research aims that are being addressed with existing data, new or advanced methods of analyses, or novel combinations and integration of datasets that allow the exploration of important scientific questions in cancer research.

Through this Notice of Funding Opportunity (NOFO), the National Cancer Institute (NCI) intends to stimulate translation of scientific discoveries and engineering developments in imaging, data science and/or spectroscopic technologies into methods or tools that address contemporary problems in understanding the fundamental biology, potential risk of development, diagnosis, treatment, and/or disease status for cancer or other disease.

Awarded activities will facilitate the translation of novel recording and modulation technologies that can be used to treat and/or diagnose central nervous system (CNS) diseases and disorders and to better understand the human CNS, from proof of concept up to the stage of readiness for first in human (FIH) studies. Technologies may incorporate any signal modality (e.g., electrical, optical, magnetic, acoustic) or a combination thereof. Diverse team-based applications that integrate appropriate domains of expertise are encouraged.

Through this Notice of Funding Opportunity (NOFO), the National Cancer Institute (NCI) along with other participating Institutes encourages submission of applications proposing to conduct secondary data analysis and integration of existing datasets and database resources, with the ultimate aim to elucidate cancer risk and related outcomes (e.g., risk prediction or reduction, survival, or response to treatment, etc.). The goal of this initiative is to address key scientific questions relevant to cancer by supporting the analysis of existing clinical, environmental, surveillance, health services, vital statistics, behavioral, lifestyle, genomic, and molecular profiles data. Applicants are encouraged to leverage and perform innovative analyses of the existing data. Applications may include new research aims that are being addressed with existing data, new or advanced methods of analyses, or novel combinations and integration of datasets that allow the exploration of important scientific questions in cancer research.

The National Human Genome Research Institute (NHGRI) is publishing a Notice of Funding Opportunity (NOFO) to solicit applications for the Impact of Genomic Variation on Function (IGVF) Data and Coordinating Center (DACC). The DACC will serve as the coordinating center for the IGVF Consortium and will be responsible for expanding and further developing a broadly accessible set of resources, including a data portal and a comprehensive and searchable catalog of measured and predicted variant impacts. The DACC will also seek input on the design of the catalog from the broader research community, organize and facilitate consortium activities, and seek opportunities to work with other programs and consortia. As a member of IGVF, the DACC will work with all consortium members to maximize the consortium's overall scientific impact and contribute to accelerating understanding of genomic variation.

The purpose of this Notice of Funding Opportunity (NOFO) is to solicit applications to characterize genomic variation to assess the impact of individual variants on genome function. This will be accomplished by systematically perturbing variants or elements using one or more high-throughput methods; collecting data on the effects of variants in DNA, RNA, or protein-coding elements on molecular, cellular, or organismal phenotypes; and developing robust, reproducible, and portable data processing pipelines. Centers funded through this initiative will become a part of the Impact of Genomic Variation on Function (IGVF) Consortium. As consortium members, centers will work together to ensure all consortium resources are accessible to a wide variety of potential users. Centers are also expected to collaborate with other consortium components to coordinate assays, variants, and cell types, and to develop shared analysis strategies to meet consortium goals.

The purpose of this Notice of Funding Opportunity (NOFO) is to solicit applications to study the effects of genetic or environmental interactions on genomic variant impact. To accomplish this, interaction centers will first propose a research framework to investigate whether interactions with effects beyond additive are important modifiers of the impact of variants. Centers will apply their framework to experimentally test combinations for interactions and share their data as well as analyses through the Impact of Genomic Variation on Function (IGVF) portal and catalog. Centers will share their method for predicting the most important combinations for future testing. The rationale for this combination of research and resource work is the identification of a structure within the interaction landscape might result in better predictions of the most important interactions to test, leading to more effective variant testing, better understanding of genome-wide association studies (GWAS), and improved polygenic scores. As IGVF Consortium members, centers will work together to ensure all consortium resources are accessible to a wide variety of potential users. Centers are also expected to collaborate with other consortium components to coordinate assays, variants, and cell types, and to develop shared analysis strategies to meet consortium goals.

The Genomics Research to Elucidate the Genetics of Rare Diseases:innovation (GREGoRi) initiative seeks to accelerate a paradigm shift in rare disease diagnosis by reimagining the tools, molecular technologies and analytical approaches used to identify the causal gene(s) and/or variant(s) underlying rare genetic disorders. The purpose of this Notice of Funding Opportunity is to establish the GREGoRi Technology Integration Center, which will enable the development of standards and best practices for applying new and emerging molecular methods in rare disease diagnosis. A major deliverable of the Center will be a multidimensional dataset that can be used for the development and benchmarking of novel tools and strategies that facilitate rare disease diagnosis.