SOHSite: incorporating evolutionary information and physicochemical properties to identify protein S-sulfenylation sites

Distribution of KEGG pathway annotations for S-sulfenylated proteins. (DOCX 15 kb

A study on the flexibility of enzyme active sites

<p>Abstract</p> <p>Background</p> <p>A common assumption about enzyme active sites is that their structures are highly conserved to specifically distinguish between closely similar compounds. However, with the discovery of distinct enzymes with similar reaction chemistries, more and more studies discussing the structural flexibility of the active site have been conducted.</p> <p>Results</p> <p>Most of the existing works on the flexibility of active sites focuses on a set of pre-selected active sites that were already known to be flexible. This study, on the other hand, proposes an analysis framework composed of a new data collecting strategy, a local structure alignment tool and several physicochemical measures derived from the alignments. The method proposed to identify flexible active sites is highly automated and robust so that more extensive studies will be feasible in the future. The experimental results show the proposed method is (a) consistent with previous works based on manually identified flexible active sites and (b) capable of identifying potentially new flexible active sites.</p> <p>Conclusions</p> <p>This proposed analysis framework and the former analyses on flexibility have their own advantages and disadvantage, depending on the cause of the flexibility. In this regard, this study proposes an alternative that complements previous studies and helps to construct a more comprehensive view of the flexibility of enzyme active sites.</p

Climate change and food security in East Asia

Climate change causes serious food security risk for East Asian countries. The United Nations Framework Convention on Climate Change (UNFCCC) has recognized that the climate change will impact agriculture and all nations should prepare adaptations to the impacts on food security. This article reviews the context of adaptation rules and current policy development in East Asian region. The UNFCCC and Kyoto Protocol have established specific rules for countries to develop national or regional adaptation policies and measurements. The current development of the ASEAN Strategic Plan on food security is inspiring, but the commitments to implementation by its members remain an issue of concern. We suggest that the UNFCCC enhances co-operation with the Food and Agriculture Organization (FAO) and other international organizations to further develop methodologies and technologies for all parties. Our findings suggest that agriculture is one of the most vulnerable sectors in terms of risks associated with climate change and distinct programmatic initiatives are necessary. It&apos;s imperative to promote co-operation among multilateral organizations, including the UNFCCC, FAO, World Health Organization, and others

Transformer-based Variable-rate Image Compression with Region-of-interest Control

This paper proposes a transformer-based learned image compression system. It is capable of achieving variable-rate compression with a single model while supporting the region-of-interest (ROI) functionality. Inspired by prompt tuning, we introduce prompt generation networks to condition the transformer-based autoencoder of compression. Our prompt generation networks generate content-adaptive tokens according to the input image, an ROI mask, and a rate parameter. The separation of the ROI mask and the rate parameter allows an intuitive way to achieve variable-rate and ROI coding simultaneously. Extensive experiments validate the effectiveness of our proposed method and confirm its superiority over the other competing methods.Comment: Accepted to IEEE ICIP 202

Protemot: prediction of protein binding sites with automatically extracted geometrical templates

Geometrical analysis of protein tertiary substructures has been an effective approach employed to predict protein binding sites. This article presents the Protemot web server that carries out prediction of protein binding sites based on the structural templates automatically extracted from the crystal structures of protein–ligand complexes in the PDB (Protein Data Bank). The automatic extraction mechanism is essential for creating and maintaining a comprehensive template library that timely accommodates to the new release of PDB as the number of entries continues to grow rapidly. The design of Protemot is also distinctive by the mechanism employed to expedite the analysis process that matches the tertiary substructures on the contour of the query protein with the templates in the library. This expediting mechanism is essential for providing reasonable response time to the user as the number of entries in the template library continues to grow rapidly due to rapid growth of the number of entries in PDB. This article also reports the experiments conducted to evaluate the prediction power delivered by the Protemot web server. Experimental results show that Protemot can deliver a superior prediction power than a web server based on a manually curated template library with insufficient quantity of entries. Availability:

Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency

<p>Abstract</p> <p>Background</p> <p>Investigation of metagenomes provides greater insight into uncultured microbial communities. The improvement in sequencing technology, which yields a large amount of sequence data, has led to major breakthroughs in the field. However, at present, taxonomic binning tools for metagenomes discard 30-40% of Sanger sequencing data due to the stringency of BLAST cut-offs. In an attempt to provide a comprehensive overview of metagenomic data, we re-analyzed the discarded metagenomes by using less stringent cut-offs. Additionally, we introduced a new criterion, namely, the evolutionary conservation of adjacency between neighboring genes. To evaluate the feasibility of our approach, we re-analyzed discarded contigs and singletons from several environments with different levels of complexity. We also compared the consistency between our taxonomic binning and those reported in the original studies.</p> <p>Results</p> <p>Among the discarded data, we found that 23.7 ± 3.9% of singletons and 14.1 ± 1.0% of contigs were assigned to taxa. The recovery rates for singletons were higher than those for contigs. The <it>Pearson </it>correlation coefficient revealed a high degree of similarity (0.94 ± 0.03 at the phylum rank and 0.80 ± 0.11 at the family rank) between the proposed taxonomic binning approach and those reported in original studies. In addition, an evaluation using simulated data demonstrated the reliability of the proposed approach.</p> <p>Conclusions</p> <p>Our findings suggest that taking account of conserved neighboring gene adjacency improves taxonomic assignment when analyzing metagenomes using Sanger sequencing. In other words, utilizing the conserved gene order as a criterion will reduce the amount of data discarded when analyzing metagenomes.</p

TransTIC: Transferring Transformer-based Image Compression from Human Visualization to Machine Perception

This work aims for transferring a Transformer-based image compression codec from human vision to machine perception without fine-tuning the codec. We propose a transferable Transformer-based image compression framework, termed TransTIC. Inspired by visual prompt tuning, we propose an instance-specific prompt generator to inject instance-specific prompts to the encoder and task-specific prompts to the decoder. Extensive experiments show that our proposed method is capable of transferring the codec to various machine tasks and outshining the competing methods significantly. To our best knowledge, this work is the first attempt to utilize prompting on the low-level image compression task

Increasing utilization of Internet-based resources following efforts to promote evidence-based medicine: a national study in Taiwan

BACKGROUND: Since the beginning of 2007, the National Health Research Institutes has been promoting the dissemination of evidence-based medicine (EBM). The current study examined longitudinal trends of behaviors in how hospital-based physicians and nurses have searched for medical information during the spread of EBM. METHODS: Cross-sectional postal questionnaire surveys were conducted in nationally representative regional hospitals of Taiwan thrice in 2007, 2009, and 2011. Demographic data were gathered concerning gender, age, working experience, teaching appointment, academic degree, and administrative position. Linear and logistic regression models were used to examine predictors and changes over time. RESULTS: Data from physicians and nurses were collected in 2007 (n = 1156), 2009 (n = 2975), and 2011 (n = 3999). There were significant increases in the use of four Internet-based resources – Web portals, online databases, electronic journals, and electronic books – across the three survey years among physicians and nurses (p < 0.001). Access to textbooks and printed journals, however, did not change over the 4-year study period. In addition, there were significant relationships between the usage of Internet-based resources and users’ characteristics. Age and faculty position were important predictors in relation to the usage among physicians and nurses, while academic degree served as a critical factor among nurses only. CONCLUSIONS: Physicians and nurses used a variety of sources to look for medical information. There was a steady increase in use of Internet-based resources during the diffusion period of EBM. The findings highlight the importance of the Internet as a prominent source of medical information for main healthcare professionals

UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy

In this work, we tackle the problem of learning universal robotic dexterous grasping from a point cloud observation under a table-top setting. The goal is to grasp and lift up objects in high-quality and diverse ways and generalize across hundreds of categories and even the unseen. Inspired by successful pipelines used in parallel gripper grasping, we split the task into two stages: 1) grasp proposal (pose) generation and 2) goal-conditioned grasp execution. For the first stage, we propose a novel probabilistic model of grasp pose conditioned on the point cloud observation that factorizes rotation from translation and articulation. Trained on our synthesized large-scale dexterous grasp dataset, this model enables us to sample diverse and high-quality dexterous grasp poses for the object point cloud.For the second stage, we propose to replace the motion planning used in parallel gripper grasping with a goal-conditioned grasp policy, due to the complexity involved in dexterous grasping execution. Note that it is very challenging to learn this highly generalizable grasp policy that only takes realistic inputs without oracle states. We thus propose several important innovations, including state canonicalization, object curriculum, and teacher-student distillation. Integrating the two stages, our final pipeline becomes the first to achieve universal generalization for dexterous grasping, demonstrating an average success rate of more than 60\% on thousands of object instances, which significantly outperforms all baselines, meanwhile showing only a minimal generalization gap.Comment: Accepted to CVPR 202