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An integrated approach to infer cross-talks between intracellular protein transport and signaling pathways

Overview of attention for article published in BMC Bioinformatics, March 2018
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Title
An integrated approach to infer cross-talks between intracellular protein transport and signaling pathways
Published in
BMC Bioinformatics, March 2018
DOI 10.1186/s12859-018-2036-2
Pubmed ID
Authors

Kumar Parijat Tripathi, Marina Piccirillo, Mario Rosario Guarracino

Abstract

The endomembrane system, known as secretory pathway, is responsible for the synthesis and transport of protein molecules in cells. Therefore, genes involved in the secretory pathway are essential for the cellular development and function. Recent scientific investigations show that ER and Golgi apparatus may provide a convenient drug target for cancer therapy. On the other hand, it is known that abundantly expressed genes in different cellular organelles share interconnected pathways and co-regulate each other activities. The cross-talks among these genes play an important role in signaling pathways, associated to the regulation of intracellular protein transport. In the present study, we device an integrated approach to understand these complex interactions. We analyze gene perturbation expression profiles, reconstruct a directed gene interaction network and decipher the regulatory interactions among genes involved in protein transport signaling. In particular, we focus on expression signatures of genes involved in the secretory pathway of MCF7 breast cancer cell line. Furthermore, network biology analysis delineates these gene-centric cross-talks at the level of specific modules/sub-networks, corresponding to different signaling pathways. We elucidate the regulatory connections between genes constituting signaling pathways such as PI3K-Akt, Ras, Rap1, calcium, JAK-STAT, EFGR and FGFR signaling. Interestingly, we determine some key regulatory cross-talks between signaling pathways (PI3K-Akt signaling and Ras signaling pathway) and intracellular protein transport.

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 18%
Student > Master 5 18%
Student > Doctoral Student 2 7%
Student > Ph. D. Student 2 7%
Unspecified 1 4%
Other 3 11%
Unknown 10 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 25%
Medicine and Dentistry 4 14%
Agricultural and Biological Sciences 2 7%
Chemical Engineering 1 4%
Unspecified 1 4%
Other 2 7%
Unknown 11 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 May 2023.
All research outputs
#16,361,564
of 24,877,869 outputs
Outputs from BMC Bioinformatics
#5,263
of 7,601 outputs
Outputs of similar age
#207,617
of 338,018 outputs
Outputs of similar age from BMC Bioinformatics
#76
of 112 outputs
Altmetric has tracked 24,877,869 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,601 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 338,018 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 112 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.