Bioinformatics, Data Analytics and Predictive Modeling

生物信息学、数据分析和预测建模核心的总体目标是支持我们的用户 信息学需求，并为成瘾和神经科学领域创造创新的信息学资源 促进我们对细胞-细胞信号、药物成瘾和药物暴露过程的理解。高- 吞吐量多肽组学、蛋白质组学、代谢组学、转录组学和基因组学研究促进了我们的 了解与健康和疾病相关的分子过程，包括测序， 鉴定和分析多肽、蛋白质、蛋白质组合、代谢物、转录本和基因。这个 这些信息的整合加强了对潜在的分子途径的表征 接触滥用药物。研究蛋白质和多肽的复杂混合物带来的挑战，以及 通过分析来自多肽、蛋白质和转录物异构体以及基因的大量数据。这些 在研究神经肽时，由于其复杂的转录后和后转录后反应，挑战被放大 转换处理。研究神经递质、蛋白质、蛋白质复合体和代谢物 可比的挑战。我们核心的坚定使命是开发和促进强健和敏感的 促进对与药物暴露和细胞相关的分子过程的理解的分析工具 发信号。我们已经成为注释、预测和表征的主要资源 神经肽和蛋白质形式，通过公共资源库和开源发现分享我们的发现 工具。我们的使命是通过(A)开发所需的生物信息学资源；以及(B)与 辅助用户使用的采样分离核心和分子图谱表征核心 生物信息学问题，包括实验设计；高级分析、基准和交叉验证； 以及对研究结果的可视化。针对目前生物信息学的局限性，提出了四个目标：(1) 严格鉴定多肽和蛋白质；(2)准确检测和定量与之相关的多肽 细胞-细胞信号传递；(3)增强了驱动分子的特性和与以下相关的分子关系 细胞信号和药物暴露；(4)蛋白质形式和数量的精确表征和量化 与细胞-细胞信号和DUG暴露相关的蛋白质复合体。拟议的努力中心的意义 关于生物信息学资源的开发，将提高多肽、蛋白质、 通过整合鉴定蛋白质形式、蛋白质复合体、代谢物和转录本 多种多样的信息。开发的方法将应用于增强我们对成瘾的理解- 相关路径，并与神经科学界共享。

The overarching goal of the Bioinformatics, Data Analytics and Predictive Modeling Core is to support our users' informatics needs and to create innovative informatics resources for the addiction and neuroscience fields to advance our understanding of the cell-cell signaling, drug addiction and drug exposure processes. High- throughput peptidomics, proteomics, metabolomics, transcriptomics, and genomics studies advance our understanding of the molecular processes associated with health and disease, and encompass sequencing, identification, and profiling of peptides, proteins, protein assemblies, metabolites, transcripts, and genes. The integration of this information strengthens the characterization of molecular pathways underlying the effects of exposure to drugs of abuse. Challenges arise from examining complex mixtures of proteins and peptides, and from analyzing massive volumes of data from peptides, protein and transcript isoforms, and genes. These challenges are magnified when studying neuropeptides because of their complex post-transcriptional and post- translational processing. Studying neurotransmitters, proteins, protein complexes, and metabolites present comparable challenges. Our Core's steadfast mission is to develop and facilitate the use of robust and sensitive analytical tools to advance the understanding of molecular processes associated with drug exposure and cell signaling. We have become a premier resource for the annotation, prediction, and characterization of neuropeptides and proteoforms while sharing our findings through public repositories and open source discovery tools. Our mission is accomplished by (a) developing needed bioinformatics resources; and (b) collaborating with the Sampling and Separation Core and the Molecular Profiling and Characterization Core in assisting users on bioinformatics matters, including experimental design; advanced analysis, benchmarking, and cross-validation; and visualization of the findings. Addressing present bioinformatic limitations, four Aims are proposed: (1) rigorous identification of peptides and proteins; (2) precise detection and quantification of the peptides linked to cell-cell signaling; (3) enhanced characterization of driver molecules and molecular relationships associated with cell signaling and drug exposure; and (4) precise characterization and quantification of the proteoforms and protein complexes linked to cell-cell signaling and dug exposure. The significance of the proposed efforts centers on the development of bioinformatics resources that will improve the accuracy and precision of peptide, protein, proteoform, protein complex, metabolite, and transcript identification and characterization through the integration of multi-omic information. The developed approaches will be applied to augment our understanding of addiction- associated pathways and shared with the neuroscience community.