ArticleMolecular biology of the cell2015
Implications of Big Data for cell biology.
Article in Molecular biology of the cell, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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.
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Who cites it
20 citing papers in PubMed.
- A Multi-Omics, Machine Learning-Aware, Genome-Wide Metabolic Model of Bacillus Subtilis Refines the Gene Expression and Cell Growth Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- MOBILE pipeline enables identification of context-specific networks and regulatory mechanisms.Nature communications · 2023Article
- Quantifying Yeast Microtubules and Spindles Using the Toolkit for Automated Microtubule Tracking (TAMiT).Biomolecules · 2023Article
- Community development, implementation, and assessment of a NIBLSE bioinformatics sequence similarity learning resource.PloS one · 2021Article
- Identification of early liver toxicity gene biomarkers using comparative supervised machine learning.Scientific reports · 2020Article
- Emergence of informative higher scales in biological systems: a computational toolkit for optimal prediction and control.Communicative & integrative biology · 2020Article
- Simultaneous cross-evaluation of heterogeneousScience (New York, N.Y.) · 2020Article
- Article
- Handling Big Data Scalability in Biological Domain Using Parallel and Distributed Processing: A Case of Three Biological Semantic Similarity Measures.BioMed research international · 2019Article
- Machine-learning-based patient-specific prediction models for knee osteoarthritis.Nature reviews. Rheumatology · 2019Review
- Sea Spray Aerosol: Where Marine Biology Meets Atmospheric Chemistry.ACS central science · 2018Review
- Interpretation of an individual functional genomics experiment guided by massive public data.Nature methods · 2018Article
- Analysis of public RNA-sequencing data reveals biological consequences of genetic heterogeneity in cell line populations.Scientific reports · 2018Article
- Article
- Cell Cycle Model System for Advancing Cancer Biomarker Research.Scientific reports · 2017Article
- The frontier of data discoverability: Why we need to share our data.Applications in plant sciences · 2017Article
- Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics.Progress in nuclear magnetic resonance spectroscopy · 2017Review
- Scalability and Validation of Big Data Bioinformatics Software.Computational and structural biotechnology journal · 2017Review
- BiGG Models: A platform for integrating, standardizing and sharing genome-scale models.Nucleic acids research · 2016Article
- Interdisciplinary innovations are key to effective use of quantitative biological information.Molecular biology of the cell · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
"Big Data" has surpassed "systems biology" and "omics" as the hottest buzzword in the biological sciences, but is there any substance behind the hype? Certainly, we have learned about various aspects of cell and molecular biology from the many individual high-throughput data sets that have been published in the past 15-20 years. These data, although useful as individual data sets, can provide much more knowledge when interrogated with Big Data approaches, such as applying integrative methods that leverage the heterogeneous data compendia in their entirety. Here we discuss the benefits and challenges of such Big Data approaches in biology and how cell and molecular biologists can best take advantage of them.
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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.