12 L Platform 1 model codes
Ontology highlight
ABSTRACT:
SUBMITTER: 
David Nickerson
PROVIDER: 6b0 | Physiome Model Repository |
REPOSITORIES: PMR
Similar Datasets
Project description:Stringtie, developed at the Center for Computational Biology at Johns Hopkins University.
| PRJNA247362 | ENA
Project description:Artificial intelligence has significantly advanced computational biology. Recent developments in omics technologies, such as single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST), provide detailed genomic data alongside tissue histology. However, current computational models often focus on either omics- or image-based analysis, lacking integration of both. To address this, we developed OmiCLIP, a visual-omics foundation model linking hematoxylin and eosin (H&E) images and transcriptomics using tissue patches from Visium data. For transcriptomics, we created 'sentences' by concatenating top-expressed gene symbols from tissue patches. We curated a dataset of 2.2 million paired tissue images and transcriptomic data across 32 organs to train OmiCLIP integrating histology and transcriptomics. Building on OmiCLIP, we created the Loki platform, which offers five key functions: tissue alignment, tissue annotation based on bulk RNA-seq or marker genes, cell type decomposition, image–transcriptomics retrieval, and ST gene expression prediction from H&E images. Compared with 22 state-of-the-art models on 5 simulations, 19 public, and 4 in-house experimental datasets, Loki demonstrated consistent accuracy and robustness in all tasks.
2025-04-01 | GSE293199 | GEO
Project description:<p>The overall aim of this study is to investigate the role of impulsivity as an endophenotype for drug addiction. Although impulsivity is considered one of the strongest candidate endophenotypes for addiction, progress in the field is hampered by the heterogeneity of impulsivity, characterized by multiple personality, psychiatric, and neurocognitive dimensions, rarely examined concurrently in the same population; and the heterogeneity of addiction phenotypes, due in part to the high rates of polysubstance dependence among substance users. To address these challenges, we have developed a program of addiction research in Bulgaria, a key transit country for heroin trafficking due to its strategic geographical location on the "Balkan Drug Route" and a major European center for production of synthetic amphetamine-type stimulants. This has allowed us to access rare populations of predominantly mono-substance dependent heroin and amphetamine users, many in protracted abstinence. Our preliminary results reveal a complex relationship between trait and neurocognitive (state) dimensions of impulsivity, often manifested in opposite directions in heroin and amphetamine dependent individuals. Pilot computational modeling analyses of decision-making, a central neurocognitive aspect of impulsivity, have proved particularly informative by indicating that different mechanisms may underlie the impaired decision-making of opiate and stimulant users. A different modeling approach, i.e. phenotypic modeling, holds significant promise to address the pervasive "missing heritability" problem in genetic studies. While genetic heterogeneity is often invoked as an explanation, the manner in which complex phenotypic traits are measured and modeled is equally important contributor to the missing heritability problem but has received much less attention in the literature. Despite the multidimensionality of traits measured by psychometric, diagnostic, and neurocognitive instruments, most GWAS studies typically use aggregate sum scores that do not reflect the underlying phenotypic multidimensionality. Therefore, at least part of the missing heritability problem may originate in misspecification of the phenotypic models. Consequently, sample sizes requirements may increase from ~800 subjects in correctly specified models to 6,000-16,000 subjects in incorrectly specified models. The current study aims to increase our understanding of the complex relationship between multiple putative impulsivity endophenotypes to help redefine endophenotypes as multi-level combination of measures that could inform multivariate multilevel models of complex phenotypes. The specific aims of the study are to: (1) Assess the utility of various personality, psychiatric, and neurocognitive indices of impulsivity (either individually or in combination) as candidate endophenotype(s) for drug addiction in general and for opiate and stimulant addictions in particular; (2) Evaluate the viability of computational model parameters modeling various neurocognitive dimensions of impulsivity as novel endophenotype(s) for addiction; and (3) Test the external validity of the optimal endophenotype(s) by evaluating their associations with HIV and other risk behaviors in opiate and stimulant users in protracted abstinence, a question of critical importance for prevention and intervention efforts in this much less-well understood stage of the addiction cycle. </p>
| phs001647 | dbGaP
Project description:The tetrameric tumor suppressor p53 represents a great challenge for 3D structural analysis due to its high degree of intrinsic disorder (ca. 40%). We developed and applied an integrative structural biology approach combining complementary techniques of structural mass spectrometry (MS), namely cross-linking mass spectrometry (XL-MS), protein footprinting, and hydrogen/deuterium exchange mass spectrometry (HDX-MS), with advanced protein structure prediction approaches to gain insights into the disordered C-terminal region of p53. Additionally, we evaluate possible differences in p53 regarding solvent accessibility and topology upon DNA binding. Our quantitative XL-MS and lysine labeling data show no major conformational differences in p53 between DNA-bound and DNA-free states. Integration of experimental data generate p53 models for p53’s intrinsically disordered regions (IDRs) that reflect substantial compaction of the molecule. Our models provide the most detailed description of the relationship between p53’s folded regions and IDRs that is available to date. The synergies between complementary structural MS techniques and computational modeling as pursued in our integrative approach is envisioned to serve as general strategy for studying intrinsically disordered proteins (IDPs) and IDRs.
2023-06-26 | PXD037030 | Pride
Project description:To understand the current situation of the postoperative gastrointestinal dysfunction in patients with colorectal cancer effect a radical cure, and analyze the risk factors, and build the colorectal cancer radical surgery in patients with gastrointestinal dysfunction risk prediction nomogram model decision tree classification and regression tree model, through internal validation evaluation the performance of the two models in the modeling data set and dividing the postoperative gastrointestinal dysfunction risk level.Two risk prediction models were used to carry out external verification, evaluate the clinical practicability and effectiveness of the model, and provide reference for further promotion of the model.
| 62483 | ecrin-mdr-crc
Project description:Oral mucosa of smokers is subject to cigarette smoke (CS)-related cytological, genomic, and transcriptional changes that could potentially lead to the development of mouth diseases. In order to further characterize CS effects, we took advantage of two human organotypic in vitro models of the buccal and gingival epithelia (MatTek(R)) that have been developed from the same donor (healthy, non-smoker) to reflect the in vivo situation. Both gingival and buccal organotypic cultures were exposed to fresh, diluted CS at the air-liquid interface in parallel and 4 times (one conventional reference cigarette 3R4F at a time, 1 h intervals, CS dilution with air: 0.46 L/min or 0.16 L/min resulting in CS concentrations of 19.7% and 40.7% (v/v) respectively. Gene expression was captured at time 0 h following the 4th exposure and after different post-exposure time points (4h, 24h, 48h) to investigate time- and concentration-dependent CS effect on both tissues. Other endpoints (e.g. cytotoxicity, pro-inflammatory marker release, cytochrome P450 (CYP) activity, immunohistology) were also measured for some time points. By using computational approaches and by capturing systems biology endpoints, various perturbations of biological processes (e.g. inflammation, cell proliferation, cellular stress) triggered by repeated exposure to CS were analyzed in both buccal and gingival in vitro models. We describe here for the first time the impact of whole CS exposure on human buccal and gingival organotypic in vitro models using various approaches combining systems biology, biological network models, computational methods and standard endpoints.
2014-08-30 | E-MTAB-2251 | biostudies-arrayexpress
Project description:A major goal of systems biology is the development of models that accurately predict responses of a cell or organism to perturbation. Constructing such models requires collection of dense measurements of system states, yet transformation of the data into predictive constructs remains a challenge. As a first step towards modeling human immunity, we have analyzed immune parameters in depth both at baseline and in response to perturbation with influenza vaccination. Peripheral blood cell transcriptomes, serum titers, frequencies of 126 cell subpopulations, and B cell responses were assessed before and after vaccination in 63 individuals and used to develop a systematic, computational framework to dissect inter- and intra-individual variation and build predictive models of post-vaccination antibody responses. Strikingly, independent of age and pre-existing antibody titers, accurate models could be constructed using pre-perturbation parameters alone, which were validated using data from independent baseline time-points. Most of the parameters contributing to prediction delineated temporally-stable baseline differences across individuals, raising the prospect of immune responsiveness prediction before intervention. According to CHI protocol 09-H1-0239, PBMC samples from 63 healthy voluntiers were collected 7 days prior to vaccination, immediately before vaccination (day0), and at 3 time points (day1, day7 and day70) post vaccination. The CHI Consortium
2014-04-10 | E-GEOD-47353 | biostudies-arrayexpress
Project description:Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have been widely used for disease modeling and drug cardiotoxicity screening. To this end, we recently developed human cardiac organoids (hCOs) for modeling human myocardium. Here, we perform a transcriptomic analysis of various in vitro hiPSC-CM platforms (2D iPSC-CM, 3D iPSC-CM and hCOs) to deduce strengths and limitations of these in vitro models. We further compared iPSC-CM models to human myocardium samples. Our data shows that the 3D in vitro environment of 3D hiPSC-CMs and hCOs stimulates expression of genes associated with tissue formation. hCOs demonstrated diverse physiologically relevant cellular functions compared to hiPSC-CM only models. Including other cardiac cell types within hCOs led to more transcriptomic similarly to adult myocardium. hCOs lack matured cardiomyocytes and immune cells which limits a complete replication of human adult myocardium. In conclusion, 3D hCOs are transcriptomically similar to myocardium, and future developments of engineered 3D cardiac models would benefit from diversifying cell populations, especially immune cells.
2021-08-31 | GSE181397 | GEO
Project description:MicroRNAs (miRNAs) are small non-coding RNAs that play essential roles in plant growth and development. We conducted a genome-wide survey of maize miRNA genes, characterizing their structure, expression, and evolution. Computational approaches based on homology and secondary structure modeling identified 150 high-confidence genes within 26 miRNA families. For 25 families, expression was verified by deep-sequencing of small RNA libraries that were prepared from an assortment of maize tissues. PCR-RACE amplification of 68 miRNA transcript precursors, representing 18 families conserved across several plant species, showed that splice variation and the use of alternative transcriptional start and stop sites is common within this class of genes. Comparison of sequence variation data from diverse maize inbred lines versus teosinte accessions suggest that the mature miRNAs are under strong purifying selection while the flanking sequences evolve equivalently to other genes. Since maize is derived from an ancient tetraploid, the effect of whole-genome duplication on miRNA evolution was examined. We found that, like protein-coding genes, duplicated miRNA genes underwent extensive gene-loss, with ~35% of duplicate homeologous miRNA genes retained. This number is higher than that observed with protein-coding genes. A search for putative miRNA targets indicated a bias towards genes in regulatory and metabolic pathways. As maize is one of the principal models for plant growth and development, this study will serve as a foundation for future research into the functional roles of miRNA genes. Surveying miRNA genes in 5 maize tissues (root, seedling, tassel, ear, and pollen) by sequencing small RNA libraries using the Illumina Genome Analyzer
2009-11-23 | E-GEOD-17943 | biostudies-arrayexpress
Project description:The Toll-like receptor and chemotaxis pathways are key components of the innate immune system. Computational modeling and simulation at the molecular interaction level can be used to study complex biological pathways, but protein concentration values must be input as model parameters. In this investigation, targeted mass spectrometry assays were developed and used to measure the absolute abundance (copies/cell) of proteins of the mouse macrophage Toll-like receptor 4 (TLR4) and chemotaxis pathways. The data produced by this investigation can be used for pathway modeling and simulation, as well as for other systems biology research.
2022-08-15 | PXD031697 | panorama