ReviewJournal of biomedicine & biotechnology2011
Studies of complex biological systems with applications to molecular medicine: the need to integrate transcriptomic and proteomic approaches.
Review in Journal of biomedicine & biotechnology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Extremophilic Yeasts as Next-Generation Eukaryotic Models: Mechanisms of Stress Integration, Systems Biology and Biotechnological Applications: A Review.Journal of fungi (Basel, Switzerland) · 2026Review
- Reproductomics: Exploring the Applications and Advancements of Computational Tools.Physiological research · 2024Review
- Impact of Cryopreservation on Spermatozoa Freeze-Thawed Traits and Relevance OMICS to Assess Sperm Cryo-Tolerance in Farm Animals.Frontiers in veterinary science · 2021Review
- Article
- OMICS: Current and future perspectives in reproductive medicine and technology.Journal of human reproductive sciences · 2014Review
- Proteomic approaches for the study of tissue specific effects of 3,5,3'-triiodo-L-thyronine and 3,5-diiodo-L-thyronine in conditions of altered energy metabolism.Frontiers in physiology · 2014Review
- Associations between thyroid hormones and serum metabolite profiles in an euthyroid population.Metabolomics : Official journal of the Metabolomic Society · 2014Article
- Application of machine learning to proteomics data: classification and biomarker identification in postgenomics biology.Omics : a journal of integrative biology · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Omics approaches to the study of complex biological systems with potential applications to molecular medicine are attracting great interest in clinical as well as in basic biological research. Genomics, transcriptomics and proteomics are characterized by the lack of an a priori definition of scope, and this gives sufficient leeway for investigators (a) to discern all at once a globally altered pattern of gene/protein expression and (b) to examine the complex interactions that regulate entire biological processes. Two popular platforms in "omics" are DNA microarrays, which measure messenger RNA transcript levels, and proteomic analyses, which identify and quantify proteins. Because of their intrinsic strengths and weaknesses, no single approach can fully unravel the complexities of fundamental biological events. However, an appropriate combination of different tools could lead to integrative analyses that would furnish new insights not accessible through one-dimensional datasets. In this review, we will outline some of the challenges associated with integrative analyses relating to the changes in metabolic pathways that occur in complex pathophysiological conditions (viz. ageing and altered thyroid state) in relevant metabolically active tissues. In addition, we discuss several new applications of proteomic analysis to the investigation of mitochondrial activity.
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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.