ArticleTrends in pharmacological sciences2014
Lean Big Data integration in systems biology and systems pharmacology.
Article in Trends in pharmacological sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
39 citing papers in PubMed, 103 citations in OpenAlex.
- The unsolvable problem of traumatic brain injury (or how to stop wasting money in fruitless research).Surgical neurology international · 2026Review
- The molecular pathogenesis of placenta accreta spectrum disorder and its clinical applications.Archives of gynecology and obstetrics · 2025Review
- The Data Distillery: A Graph Framework for Semantic Integration and Querying of Biomedical Data.bioRxiv : the preprint server for biology · 2025Article
- GeneSetCart: assembling, augmenting, combining, visualizing, and analyzing gene sets.GigaScience · 2025Article
- Editorial: Integrative analysis for complex disease biomarker discovery.Frontiers in bioengineering and biotechnology · 2023Article
- Computational prediction and interpretation of druggable proteins using a stacked ensemble-learning framework.iScience · 2022Article
- Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque.Nature communications · 2022Article
- A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling.Nature communications · 2022Article
- Systems Modeling to Quantify Safety Risks in Early Drug Development: Using Bifurcation Analysis and Agent-Based Modeling as Examples.The AAPS journal · 2021Review
- High ELF4 expression in human cancers is associated with worse disease outcomes and increased resistance to anticancer drugs.PloS one · 2021Article
- VDR Signaling via the Enzyme NAT2 Inhibits Colorectal Cancer Progression.Frontiers in pharmacology · 2021Article
- Machine learning prediction of oncology drug targets based on protein and network properties.BMC bioinformatics · 2020Article
- Applications of Quantitative Systems Pharmacology in Model-Informed Drug Discovery: Perspective on Impact and Opportunities.CPT: pharmacometrics & systems pharmacology · 2019Article
- Establishing a distributed national research infrastructure providing bioinformatics support to life science researchers in Australia.Briefings in bioinformatics · 2019Article
- L1000 Viewer: A Search Engine and Web Interface for the LINCS Data Repository.Frontiers in genetics · 2019Article
- Massive mining of publicly available RNA-seq data from human and mouse.Nature communications · 2018Article
- Data Portal for the Library of Integrated Network-based Cellular Signatures (LINCS) program: integrated access to diverse large-scale cellular perturbation response data.Nucleic acids research · 2018Article
- Master Regulators Connectivity Map: A Transcription Factors-Centered Approach to Drug Repositioning.Frontiers in pharmacology · 2018Article
- Distributed retrieval engine for the development of cloud-deployed biological databases.BioData mining · 2018Article
- Network-Based Methods for Prediction of Drug-Target Interactions.Frontiers in pharmacology · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Data sets from recent large-scale projects can be integrated into one unified puzzle that can provide new insights into how drugs and genetic perturbations applied to human cells are linked to whole-organism phenotypes. Data that report how drugs affect the phenotype of human cell lines and how drugs induce changes in gene and protein expression in human cell lines can be combined with knowledge about human disease, side effects induced by drugs, and mouse phenotypes. Such data integration efforts can be achieved through the conversion of data from the various resources into single-node-type networks, gene-set libraries, or multipartite graphs. This approach can lead us to the identification of more relationships between genes, drugs, and phenotypes as well as benchmark computational and experimental methods. Overall, this lean 'Big Data' integration strategy will bring us closer toward the goal of realizing personalized medicine.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.