ReviewAdvances in genetics2015
Getting Down to Specifics: Profiling Gene Expression and Protein-DNA Interactions in a Cell Type-Specific Manner.
Review in Advances in genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Molecular Characterization of Testicular Germ Cell Tumors Using Tissue Microdissection.Methods in molecular biology (Clifton, N.J.) · 2021Review
- CATaDa reveals global remodelling of chromatin accessibility during stem cell differentiation in vivo.eLife · 2018Article
- The Promoter and Multiple Enhancers of the pou4f3 Gene Regulate Expression in Inner Ear Hair Cells.Molecular neurobiology · 2017Article
- Genome-Wide Approaches to Drosophila Heart Development.Journal of cardiovascular development and disease · 2016Article
- Target Gene Prediction of Transcription Factor Using a New Neighborhood-regularized Tri-factorization One-class Collaborative Filtering Algorithm.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and BiomedicineArticle
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
The majority of multicellular organisms are comprised of an extraordinary range of cell types, with different properties and gene expression profiles. Understanding what makes each cell type unique and how their individual characteristics are attributed are key questions for both developmental and neurobiologists alike. The brain is an excellent example of the cellular diversity expressed in the majority of eukaryotes. The mouse brain comprises of approximately 75 million neurons varying in morphology, electrophysiology, and preferences for synaptic partners. A powerful process in beginning to pick apart the mechanisms that specify individual characteristics of the cell, as well as their fate, is to profile gene expression patterns, chromatin states, and transcriptional networks in a cell type-specific manner, i.e., only profiling the cells of interest in a particular tissue. Depending on the organism, the questions being investigated, and the material available, certain cell type-specific profiling methods are more suitable than others. This chapter reviews the approaches presently available for selecting and isolating specific cell types and evaluates their key features.
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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.