457 citations · 528 across the 12 of their papers we have counts for
12 papers
ACC-UNet: A Completely Convolutional UNet model for the 2020s
Nabil Ibtehaz, Daisuke Kihara
This decade is marked by the introduction of Vision Transformer, a radical paradigm shift in broad computer vision. A similar trend is followed in medical imaging, UNet, one of the…
SHREC 2022: Protein-ligand binding site recognition
Luca Gagliardi, Andrea Raffo, Ulderico Fugacci +12
This paper presents the methods that have participated in the SHREC 2022 contest on protein-ligand binding site recognition. The prediction of protein-ligand binding regions is an…
On the Importance of Asymmetry for Siamese Representation Learning
Xiao Wang, Haoqi Fan, Yuandong Tian +2
Many recent self-supervised frameworks for visual representation learning are based on certain forms of Siamese networks. Such networks are conceptually symmetric with two parallel…
SHREC 2021: Classification in cryo-electron tomograms
Ilja Gubins, Marten L. Chaillet, Gijs van der Schot +20
Cryo-electron tomography (cryo-ET) is an imaging technique that allows three-dimensional visualization of macro-molecular assemblies under near-native conditions. Cryo-ET comes wit…
Using Steered Molecular Dynamic Tension for Assessing Quality of Computational Protein Structure Models
Lyman Monroe, Daisuke Kihara
The native structures of proteins, except for notable exceptions of intrinsically disordered proteins, in general take their most stable conformation in the physiological condition…
Application of Sequence Embedding in Protein Sequence-Based Predictions
Nabil Ibtehaz, Daisuke Kihara
In sequence-based predictions, conventionally an input sequence is represented by a multiple sequence alignment (MSA) or a representation derived from MSA, such as a position-speci…
SHREC 2021: Retrieval and classification of protein surfaces equipped with physical and chemical properties
Andrea Raffo, Ulderico Fugacci, Silvia Biasotti +21
This paper presents the methods that have participated in the SHREC 2021 contest on retrieval and classification of protein surfaces on the basis of their geometry and physicochemi…
EnAET: A Self-Trained framework for Semi-Supervised and Supervised Learning with Ensemble Transformations
Xiao Wang, Daisuke Kihara, Jiebo Luo +1
Deep neural networks have been successfully applied to many real-world applications. However, such successes rely heavily on large amounts of labeled data that is expensive to obta…
A Simple but Effective BERT Model for Dialog State Tracking on Resource-Limited Systems
Tuan Manh Lai, Quan Hung Tran, Trung Bui +1
In a task-oriented dialog system, the goal of dialog state tracking (DST) is to monitor the state of the conversation from the dialog history. Recently, many deep learning based me…
A Gated Self-attention Memory Network for Answer Selection
Tuan Lai, Quan Hung Tran, Trung Bui +1
Answer selection is an important research problem, with applications in many areas. Previous deep learning based approaches for the task mainly adopt the Compare-Aggregate architec…
Three-Dimensional Krawtchouk Descriptors for Protein Local Surface Shape Comparison
Atilla Sit, Daisuke Kihara
Direct comparison of three-dimensional (3D) objects is computationally expensive due to the need for translation, rotation, and scaling of the objects to evaluate their similarity.…
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Yuxiang Jiang, Tal Ronnen Oron, Wyatt T Clark +144
Background: The increasing volume and variety of genotypic and phenotypic data is a major defining characteristic of modern biomedical sciences. At the same time, the limitations i…