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Goro Terai

dblp:43/5356 · DBLP profile ↗
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9ranked-venue papers
4as first author
3since 2021 · last 2026
0000-0002-1059-2519ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 9 · 4 first-author · 3 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
8 papers
Bioinformatics and computational biology · 100%
Artificial intelligence
1 paper
Generative modeling · 100%

Topics — the 13 heaviest of 14, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
RNA design
1.122025
Deep generative model of RNAs based on variational autoencoder with context-free grammar · Bioinform. 2025
CDSfold: an algorithm for designing a protein-coding sequence with the most stable secondary structure · Bioinform. 2016
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
RNA structure prediction
1.012026
LinearCapR: linear-time computation of per-nucleotide structural-context probabilities of RNA without base-pair span limits · Bioinform. 2026
Machine learning › Generative modeling
variational autoencoder
0.912025
Deep generative model of RNAs based on variational autoencoder with context-free grammar · Bioinform. 2025
Bioinformatics and computational biology › protein dynamics
protein folding pathways
0.412020
Finding the direct optimal RNA barrier energy and improving pathways with an arbitrary energy model · Bioinform. 2020
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
RNA folding kinetics
0.412020
Finding the direct optimal RNA barrier energy and improving pathways with an arbitrary energy model · Bioinform. 2020
Bioinformatics and computational biology › genomics › viral genomics
SARS-CoV-2 genome analysis
0.312026
LinearCapR: linear-time computation of per-nucleotide structural-context probabilities of RNA without base-pair span limits · Bioinform. 2026
Bioinformatics and computational biology › genomics
viral genomics
0.312026
LinearCapR: linear-time computation of per-nucleotide structural-context probabilities of RNA without base-pair span limits · Bioinform. 2026
Bioinformatics and computational biology › synthetic biology
codon optimization
0.312017
Evolutionary design of multiple genes encoding the same protein · Bioinform. 2017
Bioinformatics and computational biology
synthetic biology
0.312017
Evolutionary design of multiple genes encoding the same protein · Bioinform. 2017
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics › RNA structure
RNA secondary structure
0.212016
CDSfold: an algorithm for designing a protein-coding sequence with the most stable secondary structure · Bioinform. 2016
Bioinformatics and computational biology › sequence analysis
RNA sequence analysis
0.112011
A detailed investigation of accessibilities around target sites of siRNAs and miRNAs · Bioinform. 2011
Bioinformatics and computational biology › genomics › microbial genomics
fungal genomics
0.112015
Ustiloxins, fungal cyclic peptides, are ribosomally synthesized in Ustilaginoidea virens · Bioinform. 2015
Bioinformatics and computational biology
gene regulation
0.012004
Predicting rules on organization of cis-regulatory elements, taking the order of elements into account · Bioinform. 2004

Methods — techniques the papers use, named apart from their topics

dynamic programming · 2.0variational autoencoder · 1.7context-free grammar · 1.7stochastic context-free grammar · 1.0beam pruning · 1.0best-first search · 0.4multi-objective genetic algorithm · 0.3zuker algorithm · 0.2homology-based gene cluster identification · 0.2genome sequence analysis · 0.2
YearPublicationVenuePosition
2026 LinearCapR: linear-time computation of per-nucleotide structural-context probabilities of RNA without base-pair span limits
abstract
MOTIVATION: RNA molecules adopt dynamic ensembles of secondary structures, where the local structural context of each nucleotide-such as whether it resides in a stem or a specific type of loop-strongly shapes molecular interactions and regulatory function. Structural-context probabilities therefore provide a more functionally informative view of RNA folding than the minimum free energy structures or base-pairing probabilities. However, existing tools either require O(N3) time or employ span-restricted approximations that omit long-range base-pairs, limiting their applicability to large and biologically important RNAs. RESULTS: We introduce LinearCapR, enabling linear-time, span-unrestricted computation of structural-context marginalized probabilities, using beam-pruned Stochastic Context Free Grammar-based computation. LinearCapR retains global ensemble features lost by span-limited methods and yields superior predictive power on bpRNA-1m(90) dataset, especially for multiloops and exterior regions, as well as long-distance stems. LinearCapR supports analysis of long RNAs, demonstrated on the full genome of SARS-CoV-2. LinearCapR provides the first base-pair-span-unrestricted, linear-time framework for RNA structural-context analysis, retaining key thermodynamic ensemble features essential for functional interpretation. It enables large-scale studies of viral genomes, long non-coding RNAs, and downstream analyses such as RNA-binding protein site prediction. AVAILABILITY AND IMPLEMENTATION: The source code of LinearCapR is available at https://github.com/hoget157/LinearCapR. The archived software release used in this work is available at Zenodo: https://doi.org/10.5281/zenodo.19450645.
Takumi Otagaki, Hiroaki Hosokawa, Tsukasa Fukunaga, Junichi Iwakiri, Goro Terai, Kiyoshi Asai
Bioinform.5
2025 Deep generative model of RNAs based on variational autoencoder with context-free grammar
abstract
MOTIVATION: RNA plays a crucial role in cellular functions, and designing functional RNA sequences is essential for both scientific exploration and bioengineering applications. Conventional RNA design approaches typically assume a shared secondary structure among designed sequences. However, even closely related RNAs can adopt different secondary structures, particularly when artificial mutations are introduced. RESULTS: We present a novel deep generative model that integrates context-free grammar (CFG) with a variational autoencoder (VAE) to generate RNA sequences while explicitly considering their individual secondary structures. In our method, RNA sequences and their structures are represented as parse trees based on CFG, which are then transformed into binary matrices for VAE training. The optimal parse tree is reconstructed using dynamic programming, ensuring structure-aware sequence generation. When evaluated on natural RNAs from the Rfam database, our model successfully generates high-quality RNA sequences. Furthermore, when applied to RNA aptazyme mutants with distinct secondary structures, our method reveals a strong correlation between the latent space representation of the VAE and self-cleaving activity. This underscores the importance of incorporating RNA-specific structural information in generative models. AVAILABILITY AND IMPLEMENTATION: https://github.com/gterai/RNAgg (archived at Zenodo: https://doi.org/10.5281/zenodo.15354990).
Goro Terai, Kiyoshi Asai
Bioinform.1
2025 PseudoknotVisualizer: Visualization of pseudoknots on three-dimensional RNA structures
abstract
We introduce the PseudoknotVisualizer, a specialized software designed to identify and visualize pseudoknots within RNA three-dimensional structures. Typically, RNA secondary structures containing pseudoknots can be decomposed into multiple pseudoknot-free layers. Our software colors the base pairs in each pseudoknot layer, enabling the visualization of pseudoknot distribution within three-dimensional structures. Specifically, users can utilize the PseudoknotVisualizer as a PyMOL extension, applying it directly to RNA molecules loaded in PyMOL. Additionally, a Command Line Interface (CLI) is provided, allowing users to generate coloring commands in Chimera or PyMOL formats, which can then be manually copied and pasted for visualization. By facilitating the clear depiction of pseudoknots in RNA tertiary structures, this tool addresses significant challenges in the identification and visualization of pseudoknots in RNA structural analysis, thereby enhancing research productivity and expanding potential applications in molecular biology. Availability and implementation: PseudoknotVisualizer is freely available at https://github.com/TakumiOtagaki/PseudoknotVisualizer.
Takumi Otagaki, Goro Terai, Kiyoshi Asai, Junichi Iwakiri
PLoS Comput. Biol.2
2020 Finding the direct optimal RNA barrier energy and improving pathways with an arbitrary energy model
abstract
MOTIVATION: RNA folding kinetics plays an important role in the biological functions of RNA molecules. An important goal in the investigation of the kinetic behavior of RNAs is to find the folding pathway with the lowest energy barrier. For this purpose, most of the existing methods use heuristics because the number of possible pathways is huge even if only the shortest (direct) folding pathways are considered. RESULTS: In this study, we propose a new method using a best-first search strategy to efficiently compute the exact solution of the minimum barrier energy of direct pathways. Using our method, we can find the exact direct pathways within a Hamming distance of 20, whereas the previous methods even miss the exact short pathways. Moreover, our method can be used to improve the pathways found by existing methods for exploring indirect pathways. AVAILABILITY AND IMPLEMENTATION: The source code and datasets created and used in this research are available at https://github.com/eukaryo/czno. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Hiroki Takizawa, Junichi Iwakiri, Goro Terai, Kiyoshi Asai
Bioinform.3
2017 Evolutionary design of multiple genes encoding the same protein
abstract
MOTIVATION: Enhancing expression levels of a target protein is an important goal in synthetic biology. A widely used strategy is to integrate multiple copies of genes encoding a target protein into a host organism genome. Integrating highly similar sequences, however, can induce homologous recombination between them, resulting in the ultimate reduction of the number of integrated genes. RESULTS: We propose a method for designing multiple protein-coding sequences (i.e. CDSs) that are unlikely to induce homologous recombination, while encoding the same protein. The method, which is based on multi-objective genetic algorithm, is intended to design a set of CDSs whose nucleotide sequences are as different as possible and whose codon usage frequencies are as highly adapted as possible to the host organism. We show that our method not only successfully designs a set of intended CDSs, but also provides insight into the trade-off between nucleotide differences among gene copies and codon usage frequencies. AVAILABILITY AND IMPLEMENTATION: Our method, named Tandem Designer, is available as a web-based application at http://tandem.trahed.jp/tandem/ . CONTACT: : [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Goro Terai, Satoshi Kamegai, Akito Taneda, Kiyoshi Asai
Bioinform.1
2016 CDSfold: an algorithm for designing a protein-coding sequence with the most stable secondary structure
abstract
MOTIVATION: An important problem in synthetic biology is to design a nucleotide sequence of an mRNA that confers a desirable expression level of a target protein. The secondary structure of protein-coding sequences (CDSs) is one potential factor that could have both positive and negative effects on protein production. To elucidate the role of secondary structure in CDSs, algorithms for manipulating secondary structure should be developed. RESULTS: We developed an algorithm for designing a CDS with the most stable secondary structure among all possible ones translated into the same protein, and implemented it as the program CDSfold. The algorithm runs the Zuker algorithm under the constraint of a given amino acid sequence. The time and space complexity is O(L(3)) and O(L(2)), respectively, where L is the length of the CDS to be designed. Although our algorithm is slower than the original Zuker algorithm, it could design a relatively long (2.7-kb) CDS in approximately 1 h. AVAILABILITY AND IMPLEMENTATION: The CDSfold program is freely available for non-commercial users as stand-alone and web-based software from http://cdsfold.trahed.jp/cdsfold/ CONTACTS: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Goro Terai, Satoshi Kamegai, Kiyoshi Asai
Bioinform.1
2015 Ustiloxins, fungal cyclic peptides, are ribosomally synthesized in Ustilaginoidea virens
abstract
MOTIVATION: Ustiloxins A and B are toxic cyclic tetrapeptides, Tyr-Val/Ala-Ile-Gly (Y-V/A-I-G), that were originally identified from Ustilaginoidea virens, a pathogenic fungus affecting rice plants. Contrary to our report that ustiloxin B is ribosomally synthesized in Aspergillus flavus, a recent report suggested that ustiloxins are synthesized by a non-ribosomal peptide synthetase in U.virens. Thus, we analyzed the U.virens genome, to identify the responsible gene cluster. RESULTS: The biosynthetic gene cluster was identified from the genome of U.virens based on homologies to the ribosomal peptide biosynthetic gene cluster for ustiloxin B identified from A.flavus. It contains a gene encoding precursor protein having five Tyr-Val-Ile-Gly and three Tyr-Ala-Ile-Gly motifs for ustiloxins A and B, respectively, strongly indicating that ustiloxins A and B from U.virens are ribosomally synthesized. AVAILABILITY AND IMPLEMENTATION: Accession codes of the U.virens and A.flavus gene clusters in NCBI are BR001221 and BR001206, respectively. Supplementary data are available at Bioinformatics online.
Takahiro Tsukui, Nozomi Nagano, Myco Umemura, Toshitaka Kumagai, Goro Terai, Masayuki Machida, Kiyoshi Asai
Bioinform.5
2011 A detailed investigation of accessibilities around target sites of siRNAs and miRNAs
abstract
MOTIVATION: The importance of RNA sequence analysis has been increasing since the discovery of various types of non-coding RNAs transcribed in animal cells. Conventional RNA sequence analyses have mainly focused on structured regions, which are stabilized by the stacking energies acting on adjacent base pairs. On the other hand, recent findings regarding the mechanisms of small interfering RNAs (siRNAs) and transcription regulation by microRNAs (miRNAs) indicate the importance of analyzing accessible regions where no base pairs exist. So far, relatively few studies have investigated the nature of such regions. RESULTS: We have conducted a detailed investigation of accessibilities around the target sites of siRNAs and miRNAs. We have exhaustively calculated the correlations between the accessibilities around the target sites and the repression levels of the corresponding mRNAs. We have computed the accessibilities with an originally developed software package, called 'Raccess', which computes the accessibility of all the segments of a fixed length for a given RNA sequence when the maximal distance between base pairs is limited to a fixed size W. We show that the computed accessibilities are relatively insensitive to the choice of the maximal span W. We have found that the efficacy of siRNAs depends strongly on the accessibility of the very 3'-end of their binding sites, which might reflect a target site recognition mechanism in the RNA-induced silencing complex. We also show that the efficacy of miRNAs has a similar dependence on the accessibilities, but some miRNAs also show positive correlations between the efficacy and the accessibilities in broad regions downstream of their putative binding sites, which might imply that the downstream regions of the target sites are bound by other proteins that allow the miRNAs to implement their functions. We have also investigated the off-target effects of an siRNA as a potential RNAi therapeutic. We show that the off-target effects of the siRNA have similar correlations to the miRNA repression, indicating that they are caused by the same mechanism. AVAILABILITY: The C++ source code of the Raccess software is available at http://www.ncrna.org/software/Raccess/ The microarray data on the measurements of the siRNA off-target effects are also available at the same site. CONTACT: [email protected]
Hisanori Kiryu, Goro Terai, Osamu Imamura, Hiroyuki Yoneyama, Kiyoshi Asai
Bioinform.2
2004 Predicting rules on organization of cis-regulatory elements, taking the order of elements into account
abstract
MOTIVATION: In eukaryotes, rules regarding organization of cis-regulatory elements are complex. They sometimes govern multiple kinds of elements and positional restrictions on elements. RESULTS: We propose a method for detecting rules, by which the order of elements is restricted. The order restriction is expressed as element patterns. We extract all the element patterns that occur in promoter regions of at least the specified number of genes. Then, we find significant patterns based on the expression similarity of genes with promoter regions containing each of the extracted patterns. When we applied our method to Saccharomyces cerevisiae, we detected significant patterns overlooked by previous methods, thus demonstrating the utility of our method for analyses of eukaryotic gene regulation. We also suggest that several types of element organization exist: (i) those in which only the order of elements is important, (ii) order and distance both are important and (iii) only the combination of elements is important. AVAILABILITY: The program for extracting element patterns is available upon request.
Goro Terai, Toshihisa Takagi
Bioinform.1