An extension of this analysis to published datasets from a number of other cancers identified that elevated expression of HSPC111 was a feature of several cancers including those of the breast, prostate, ovary, testis, liver, colon, and pancreas [ 31, 41], but this was not always associated with MYC over-expression.
I created a dataset pulling from a number of venture capital data sources, including CrunchBase, and narrowed it down to my own specifics: U.S., venture-backed companies that have had realized outcomes, both IPO and M&A, over $100 million since 2008.
The IGCC dataset suffers from a number of limitations.
Similar patterns were observed at some microsatellite loci in an earlier analysis of a dataset from a larger number of populations in the same area (see e.g. Figure 2b of [ 29]), and they may point to differences in local selection regimes that are not consistently related to altitude, or to differences in the genetic mechanism of adaptation to the same local selection regimes.
It has been challenging to discover A-to-I RNA editing sites from RNA-seq datasets for a number of reasons.
We tested the algorithm on a range of different datasets extracted from a number of documented benchmarks and test cases.
Datasets come from a number of different institutions around the world, and patient backgrounds differ.
The dataset contains microarrays from a number of experiments, shown clustered in the columns; note that sets of these may represent a time-series or experiments on similar tissues, or perturbations of genes involved in a particular process.
Our results illustrate the strength that arises from combining datasets from a large number of primary studies within the same research field.
