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BackgroundCommunalities between large sets of genes obtained from high-throughput experiments are often identified by searching for enrichments of genes with the same Gene Ontology (GO) annotations. The GO analysis tools used for these enrichment analyses assume that GO terms are independent and the semantic distances between all parent–child terms are identical, which is not true in a biological sense. In addition these tools output lists of often redundant or too specific GO terms, which are difficult to interpret in the context of the biological question investigated by the user. Therefore, there is a demand for a robust and reliable method for gene categorization and enrichment analysis.ResultsWe have developed Categorizer, a tool that classifies genes into user-defined groups (categories) and calculates p-values for the enrichment of the categories. Categorizer identifies the biologically best-fit category for each gene by taking advantage of a specialized semantic similarity measure for GO terms. We demonstrate that Categorizer provides improved categorization and enrichment results of genetic modifiers of Huntington’s disease compared to a classical GO Slim-based approach or categorizations using other semantic similarity measures.ConclusionCategorizer enables more accurate categorizations of genes than currently available methods. This new tool will help experimental and computational biologists analyzing genomic and proteomic data according to their specific needs in a more reliable manner.

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Research on the 3D culturing of cancer cells that better mimic in vivo solid tumors is important for efficient drug screening. Herein, a new platform that effectively facilitates the formation of cancer spheroids for anticancer drug screening is reported. Cytophilic graphene oxide (GO), when selectively coated on the sidewalls of micro‐wells fabricated from a cell‐adhesion‐resistive polymer, is found to efficiently initiates distinct donut‐like formation of cancer cell spheroids. Scanning electron microscopy and Raman mapping are used to analyze vertically coated GO micropatterns (vGO‐MPs) of different sizes (100–250 µm) on polymer platforms, and human liver cancer cells (HepG2), as a model cancer, are seeded on these platforms. Remarkably, the 150 µm‐sized platform is found to easily and rapidly generate 3D spheroids in the absence of cell‐adhesion proteins. In addition, owing to the unique characteristics of GO, vGO‐MPs are highly stable for long periods of time (≈1 month), even under harsh conditions (>70 °C). Moreover, the anticancer effects of two drugs (hydroxyurea and cisplatin) and the potential anticancer compound (curcumin) on HepG2 cells are demonstrated by simply measuring decreases in spheroid sizes. Hence, this new platform is highly promising as a cancer spheroid‐forming material for rapid drug screening.

By using carbon-free inorganic atomic layer involving heat treatment from 150 to 300 °C, environmentally stable and permanent modulation of the electronic and electrical properties of single-walled carbon nanotubes (SWCNTs) from p-type to ambi-polar and possibly to n-type has been demonstrated. At low heat treatment temperature, a strong p-doping effect from Au(3+) ions to CNTs due to a large difference in reduction potential between them is dominant. However at higher temperature, the gold species are thermally reduced, and thermally induced CNT-Cl finally occurs by the decomposition reaction of AuCl(3). Thus, in the AuCl(3)-doped SWCNTs treated at higher temperature, the p-type doping effect is suppressed and an n-type property from CNT-Cl is thermally induced. Thermal conversion of the majority carrier type of AuCl(3)-doped SWNTs is systematically investigated by combining various optical and electrical tools.