Robotic search for optimal cell culture in regenerative medicine.

Induced differentiation is one of the most experience- and skill-dependent experimental processes in regenerative medicine, and establishing optimal conditions often takes years. We developed a robotic AI system with a batch Bayesian optimization algorithm that autonomously induces the differentiation of induced pluripotent stem cell-derived retinal pigment epithelial (iPSC-RPE) cells. From 200 million possible parameter combinations, the system performed cell culture in 143 different conditions in 111 days, resulting in 88% better iPSC-RPE production than that obtained by the pre-optimized culture in terms of the pigmentation scores.

A Variable Scheduling Maintenance Culture Platform for Mammalian Cells.

Cell culturing is a basic experimental technique in cell biology and medical science. However, culturing high-quality cells with a high degree of reproducibility relies heavily on expert skills and tacit knowledge, and it is not straightforward to scale the production process due to the education bottleneck. Although many automated culture systems have been developed and a few have succeeded in mass production environments, very few robots are permissive of frequent protocol changes, which are often required in basic research environments.

Identification of endocrine disruptor biodegradation by integration of structure-activity relationship with pathway analysis.

We present a SAR method that can predict estrogen-like endocrine disrupting chemical (EDC) activity as well as key biodegradation steps for detoxification. This method is based on a recent graph-mining algorithm developed by Kudo et al., which generates a set of descriptors from all potent chemical fragments (including rings).

Mining frequent stem patterns from unaligned RNA sequences.

Motivation: In detection of non-coding RNAs, it is often necessary to identify the secondary structure motifs from a set of putative RNA sequences. Most of the existing algorithms aim to provide the best motif or few good motifs, but biologists often need to inspect all the possible motifs thoroughly.

Results: Our method RNAmine employs a graph theoretic representation of RNA sequences and detects all the possible motifs exhaustively using a graph mining algorithm.

Use of morphological analysis in protein name recognition.

Protein name recognition aims to detect each and every protein names appearing in a PubMed abstract. The task is not simple, as the graphic word boundary (space separator) assumed in conventional preprocessing does not necessarily coincide with the protein name boundary. Such boundary disagreement caused by tokenization ambiguity has usually been ignored in conventional preprocessing of general English.

A new serum antibody test kit (E plate) for evaluation of Helicobacter pylori eradication.

Objective: Serological antibody test have been widely performed to detect the presence of H. pylori, but they have not been used to evaluate the status of H. pylori after eradication.