UCLA Pediatric Research Education Program in Bioinformatics, Computational Biology, and Omics

加州大学洛杉矶分校生物信息学、计算生物学和组学儿科研究教育项目

• 批准号: 10629061
• 负责人: Sherin U Devaskar
• 金额: $ 16.14万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10629061
• 关键词: Address; Area; Basic Science; Big Data; Bioinformatics; Biological Sciences; Biometry; Caring; Child health care; Childhood; Clinical; Clinical Medicine; Clinical Research; Collaborations; Complex; Computational Biology; Computational Science; Congenital Abnormality; DNA Methylation; Data Analyses; Data Set; Development; Diagnosis; Discipline; Disease; Doctor of Philosophy; E-learning; Education; Education Gap; Educational Status; Educational process of instructing; Educational workshop; Endocrine System Diseases; Etiology; Faculty; Fostering; Foundational Skills; Functional disorder; Funding; Future; Genetic Diseases; Health; High-Throughput Nucleotide Sequencing; Hybrids; Immune System Diseases; Individual; Institution; Instruction; Intervention; Journals; Knowledge; Life; Life Cycle Stages; Link; Malignant Childhood Neoplasm; Malignant Neoplasms; Medical; Mentored Clinical Scientist Development Program; Mentors; Metabolic Diseases; Molecular; Organ; Pathway Analysis; Pathway interactions; Patient Care; Patients; Pediatric Research; Pediatrics; Physicians; Postdoctoral Fellow; Prevention strategy; Proteome; Research; Research Personnel; Research Support; Scholarship; Science; Scientist; Systemic disease; Talents; Techniques; Technology; Training; Training and Education; Translational Research; big biomedical data; big-data science; career; collaboratory; disorder risk; education research; educational atmosphere; epigenome; experience; flipped classroom; forging; gene network; genome sequencing; graduate medical education; interest; lectures; medical schools; member; metabolome; metagenome; microbiome analysis; multidisciplinary; new therapeutic target; next generation; pediatric department; pediatric patients; precision medicine; programs; recruit; single-cell RNA sequencing; skills; targeted treatment; tool; transcriptome; trend; undergraduate student; whole genome

PROJECT SUMMARY/ABSTRACT Bioinformatics, computational biology, and omics are important areas that have the potential to uncover new discoveries in the molecular/cellular mechanisms and gene networks that lead to congenital birth defects, metabolic and genetic disorders, organ dysfunction, disorders of the immune system, and cancer in Pediatric patients. The Department of Pediatrics, David Geffen School of Medicine at UCLA proposes to fill the gap for much needed specialized education and in-depth training of pediatric graduate medical education (GME) clinical trainees in biomedical big data analysis, promote the establishment of multidisciplinary networks and opportunities for collaboration in these specialized areas, and provide a bridge for trainees towards successful participation as clinicians or clinician-scientists in multi-disciplinary team science towards obtaining future funding for the discovery and amelioration of childhood disorders (i.e. T32, K23, K12, K08) and academic careers in diverse research pathways. This program will focus on recruiting pediatric GME trainees from diverse backgrounds, with an interest in clinician researcher or physician-scientist careers, and who have a desire to build foundational skills in big data analysis. Specifically, the program will target Pediatric residents in their 2nd or 3rd year of training and Pediatric subspecialty fellows at the start of their 2nd year of training. The 12-week program, set to occur at the start of the academic year, will include weekly didactic lectures, taught by UCLA faculty with expertise in bioinformatics, biostatistics, computational biology, and omics, covering key areas of big data science and omics, accompanied by workshops linked to the specific topic presented in the didactic lectures, and interactive journal club sessions. The interactive workshops, conducted by faculty and UCLA Quantitative and Computational Biosciences Collaboratory postdoctoral PhD fellows, will reinforce concepts from the didactic lectures through hands-on application of the knowledge via analysis of actual experimental datasets and use of statistical techniques. The journal club sessions will be in a flipped classroom format and will reinforce concepts covered in the didactic lectures and workshops to demonstrate the application of bioinformatics and computational biology technology that lead to new discovery and advancement of Pediatric patient care. The program will allow for remote access by pediatric trainees beyond the institution through virtual learning (hybrid format) and availability of educational content online. Key areas of skills building will include next generation whole genome sequencing, transcriptome, proteome, and metabolome analysis, single cell RNA sequencing, DNA methylation analysis, microbiome analysis, and gene network analysis. This program will provide a unique opportunity for pediatric GME trainees to receive more formal instruction and training in the very important areas of big data analysis and directly interact with the faculty on campus, beyond the Department of Pediatrics, with expertise in these areas who could potentially serve as research and career mentors, thus facilitating their successful academic journey.

项目总结/文摘