Yu-Wei Wu

Taipei Medical University | TMU · Graduate Institute of Biomedical Informatics

The percomorph fish clade Gobioidei are a suborder that comprises over 2,200 species distributed in nearly all aquatic habitats. To understand the genetics underlying their diversification, we sequenced and annotated the genome of the loach goby, Rhyacichthys aspro, the basal most group, and compared it with nine additional Gobioidei species. Withi...

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these lim...

This study aimed to develop and externally validate a prognostic prediction model for screening fetal growth restriction (FGR)/small for gestational age (SGA) using medical history. From a nationwide health insurance database (n=1,697,452), we retrospectively selected visits of 12-to-55-year-old females to healthcare providers. This study used mach...

Objectives Prevention of fetal growth restriction/small for gestational age is adequate if screening is accurate. Ultrasound and biomarkers can achieve this goal; however, both are often inaccessible. This study aimed to develop, validate, and deploy a prognostic prediction model for screening fetal growth restriction/small for gestational age usin...

Background: Existing proposed pathogenesis for preeclampsia (PE) was only applied for early onset subtype and did not consider pre-pregnancy and competing risks. We aimed to decipher PE subtypes by identifying related transcriptome that represents endometrial maturation and histologic chorioamnionitis. Methods: We utilized eight arrays of mRNA e...

Gut microbial proteolytic metabolism has been reportedly altered in Parkinson’s disease (PD). However, the circulating aromatic amino acids (AAA) described in PD are inconsistent. Here we aimed to investigate plasma AAA profiles in a large cohort of PD patients, and examine their correlations with clinical severity and gut microbiota changes. We en...

Background Existing proposed pathogenesis for preeclampsia (PE) was only applied for early onset subtype and did not consider pre-pregnancy and competing risks. We aimed to decipher PE subtypes by identifying related transcriptome that represents endometrial maturation and histologic chorioamnionitis. Methods We utilized eight arrays of mRNA expre...

In contemporary biomedical research, the accurate automatic detection of cells within intricate microscopic imagery stands as a cornerstone for scientific advancement. Leveraging state-of-the-art deep learning techniques, this study introduces a novel amalgamation of Fuzzy Automatic Contrast Enhancement (FACE) and the You Only Look Once (YOLO) fram...

Biofuels represent a promising path toward a future less reliant on fossil fuels. One reason why is because the components to generate biofuels can be found in ordinary waste, such as compost, where degradative microbes unleash the energy-dense sugars found in plant matter. While scouting for the hungriest degraders marks one way of boosting biofue...

Background: Predicting the resistance profiles of antimicrobial resistance (AMR) pathogens is becoming more and more important in treating infectious diseases. Various attempts have been made to build machine learning models to classify resistant or susceptible pathogens based on either known antimicrobial resistance genes or the entire gene set. H...

Abscondita cerata is the most abundant and widely distributed endemic firefly species in Taiwan and is considered a key environmental and ecological indicator organism. In this study, we report the first long-read genome sequencing of Abs. cerata sequenced by Nanopore technology. The draft genome size, 967Mb, was measured through a hybrid approach...

The traditional natural product discovery approach has accessed only a fraction of the chemical diversity in nature. The use of bioinformatic tools to interpret the instructions encoded in microbial biosynthetic genes has the potential to circumvent the existing methodological bottlenecks and greatly expand the scope of discovery. Structural predic...

Background and Objective: Deep learning is applied in medicine mostly due to its state-of-the-art performance for diagnostic imaging. Supervisory authorities also require the model to be explainable, but most explain the model after development (post hoc) instead of incorporating explanation into the design (ante hoc). This study aimed to demonstra...

The partial nitritation-anaerobic ammonium oxidation (anammox; PN-A) process has been considered a sustainable method for wastewater ammonium removal, with recent attempts to treat low-strength wastewater. However, how microbes adapt to the alternate microaerobic-anoxic operation of the process when treating low ammonium concentrations remains poor...

Recently, human activity recognition (HAR) techniques have made remarkable developments in the field of machine learning. In this paper, we classify human gestures using data collected from a curved piezoelectric sensor, including elbow movement, wrist turning, wrist bending, coughing, and neck bending. The classification process relies on data col...

Understanding genes and their underlying mechanisms is critical in deciphering how antimicrobial-resistant (AMR) bacteria withstand detrimental effects of antibiotic drugs. At the same time the genes related to AMR phenotypes may also serve as biomarkers for predicting whether a microbial strain is resistant to certain antibiotic drugs. We develope...

Background Plant cell walls are interwoven structures recalcitrant to degradation. Native and adapted microbiomes can be particularly effective at plant cell wall deconstruction. Although most understanding of biological cell wall deconstruction has been obtained from isolates, cultivated microbiomes that break down cell walls have emerged as new s...

O6-Methylguanine-DNA-methyltransferase (MGMT) promoter methylation was shown in many studies to be an important predictive biomarker for temozolomide (TMZ) resistance and poor progression-free survival in glioblastoma multiforme (GBM) patients. However, identifying the MGMT methylation status using molecular techniques remains challenging due to te...

Background: A well-known blood biomarker (soluble fms-like tyrosinase-1 [sFLT-1]) for preeclampsia, i.e., a pregnancy disorder, was found to predict severe COVID-19, including in males. True biomarker may be masked by more-abrupt changes related to endothelial instead of placental dysfunction. This study aimed to identify blood biomarkers that rep...

Background A well-known blood biomarker (soluble fms-like tyrosinase-1 [sFLT-1]) for preeclampsia, i.e., a pregnancy disorder, was found to predict severe COVID-19, including in males. True biomarker may be masked by more-abrupt changes related to endothelial instead of placental dysfunction. This study aimed to identify blood biomarkers that repre...

Background Predicting which pathogens might exhibit antimicrobial resistance (AMR) based on genomics data is one of the promising ways to swiftly and precisely identify AMR pathogens. Currently, the most widely used genomics approach is through identifying known AMR genes from genomic information in order to predict whether a pathogen might be resi...

Background Emerging evidence suggests that gut dysbiosis contributes to Parkinson’s disease (PD) by signaling through microbial metabolites. Hippuric acid (HA), indole derivatives, and secondary bile acids are among the most common gut metabolites. Objective To examine the relationship of systemic concentrations of these microbial metabolites asso...

Di-(2-ethylhexyl) phthalate (DEHP) represents the most used phthalate plasticizer with an annual production above the millions of tons worldwide. Due to its inadequate disposal, outstanding chemical stability, and extremely low solubility (3 mg/L), endocrine-disrupting DEHP often accumulates in urban estuarine sediments at concentrations above the...

Plant cell walls are interwoven structures recalcitrant to degradation. Both native and adapted microbiomes are particularly effective at plant cell wall deconstruction. Studying these deconstructive microbiomes provides an opportunity to assess microbiome performance and relate it to specific microbial populations and enzymes. To establish a syste...

Background and Objectives Short-chain fatty acids (SCFAs) are gut microbial metabolites that promote the disease process in a rodent model of Parkinson’s disease (PD), but fecal levels of SCFAs in PD patients are reduced. Simultaneous assessments of fecal and plasma SCFA levels, and their inter-relationships with the PD disease process are scarce....

Background Discerning genes crucial to antimicrobial resistance (AMR) mechanisms is becoming more and more important to accurately and swiftly identify AMR pathogenic strains. Pangenome-wide association studies (e.g. Scoary) identified numerous putative AMR genes. However, only a tiny proportion of the putative resistance genes are annotated by AMR...

Backgrounds: Influenza vaccination could decrease the risk of major cardiac events in patients with chronic obstructive pulmonary disease (COPD). However, the effects of the vaccine on decreasing the risk of ventricular arrhythmia (VA) development in such patients remain unclear. Methods: We retrospectively analyzed the data of 18,658 patients with...

The soil bacterium Psychrobacillus sp. strain AK 1817 was isolated from a tropical soil sample collected in Taiwan. Strain AK 1817 biotransforms the ergostane triterpenoid antcin K from the fungus Antrodia cinnamomea . The genome was sequenced using the PacBio RS II platform and consists of one chromosome of 4,096,020 bp, comprising 3,907 protein-c...

This protocol aims to develop, validate, and deploy a prediction model using high dimensional data by both human and machine learning. The applicability is intended for clinical prediction in healthcare providers, including but not limited to those using medical histories from electronic health records. This protocol applies diverse approaches to i...

This protocol aims to develop, validate, and deploy a prediction model using high dimensional data by both human and machine learning. The applicability is intended for clinical prediction in healthcare providers, including but not limited to those using medical histories from electronic health records. This protocol applies diverse approaches to i...

This protocol aimed to describe data transformation procedure of medical histories from electronic health records (EHRs) to historical rates by Kaplan-Meier (KM) estimation. The applicability is to extract features from real-world, time-varying data of EHRs, for developing but not limited to a machine learning prediction model. By this extraction t...

We aimed to provide a resampling protocol for dimensional reduction resulting a few latent variables. The applicability focuses on but not limited for developing a machine learning prediction model in order to improve the number of sample size in relative to the number of candidate predictors. By this feature representation technique, one can impro...

We proposed a learning algorithm for human to conduct literature and data mining for causal factor discovery. The applicability is to select features for a machine learning prediction model, including but not limited to that using real-world, time-varying data from electronic health records. This protocol is relatively quick to find potentially act...

We aimed to provide a framework that organizes internal properties of a convolutional neural network (CNN) model using non-image data to be interpretable by human. The interface was represented as ontology map and network respectively by dimensional reduction and hierarchical clustering techniques. The applicability is to implement a prediction mod...

We aimed to provide a framework that organizes internal properties of a convolutional neural network (CNN) model using non-image data to be interpretable by human. The interface was represented as ontology map and network respectively by dimensional reduction and hierarchical clustering techniques. The applicability is to implement a prediction mod...

We proposed a learning algorithm for human to conduct literature and data mining for causal factor discovery. The applicability is to select features for a machine learning prediction model, including but not limited to that using real-world, time-varying data from electronic health records. This protocol is relatively quick to find potentially act...

This protocol aimed to describe data transformation procedure of medical histories from electronic health records (EHRs) to historical rates by Kaplan-Meier (KM) estimation. The applicability is to extract features from real-world, time-varying data of EHRs, for developing but not limited to a machine learning prediction model. By this extraction t...

We aimed to provide a resampling protocol for dimensional reduction resulting a few latent variables. The applicability focuses on but not limited for developing a machine learning prediction model in order to improve the number of sample size in relative to the number of candidate predictors. By this feature representation technique, one can impro...

We sequenced and assembled the complete mitochondrial genome of Abscondita cerata from Nankang, Taipei City, Taiwan. The complete mitogenome of A. cerata is 16,964 bp long, and contains 13 protein-coding, 22 tRNA, and two rDNA genes. Nucleotide compositions of the mitogenome of the A. cerata are A: 43.93%, T: 36.74%, C: 11.05%, and G: 8.28%. The AT...

Importance Prognostic predictions of prelabor rupture of membranes lack proper sample sizes and external validation. Objective To develop, validate, and deploy statistical and/or machine learning prediction models using medical histories for prelabor rupture of membranes and the time of delivery. Design A retrospective cohort design within 2-year...

Di-(2-ethylhexyl) phthalate (DEHP) is the most widely used plasticizer worldwide, with an annual global production of more than 8 million tons. Because of its improper disposal, endocrine-disrupting DEHP often accumulates in estuarine sediments in industrialized countries at submillimolar levels, resulting in adverse effects on both ecosystems and...

It is critical to identify individual genomes from microbiomic samples in order to carry out analysis of the microbes. Methods based on existing databases, however, may have limited capabilities in elucidating and quantifying the microbes due to the largely unidentified microbial species in natural or human‐associated environments. We thus develope...

Ganoderma lucidum is a medicinal fungus whose numerous triterpenoids are its main bioactive constituents. Although hundreds of Ganoderma triterpenoids have been identified, Ganoderma triterpenoid glycosides, also named triterpenoid saponins, have been rarely found. Ganoderic acid A (GAA), a major Ganoderma triterpenoid, was synthetically cascaded t...

Di-(2-ethylhexyl) phthalate (DEHP) is the most widely used plasticizer worldwide with an annual global production of over eight million tons. Because of its improper disposal, endocrine-disrupting DEHP often accumulates in estuarine sediments in industrialized countries at sub-millimolar levels, resulting in adverse effects on both ecosystems and h...

The capability of gut microbiota in degrading foods and drugs administered orally can result in diversified efficacies and toxicity interpersonally and cause significant impact on human health. Production of atherogenic trimethylamine N-oxide (TMAO) from carnitine is a gut microbiota-directed pathway and varies widely among individuals. Here, we de...

Celastrol is a quinone-methide triterpenoid isolated from the root extracts of Tripterygium wilfordii (Thunder god vine). Although celastrol possesses multiple bioactivities, the potent toxicity and rare solubility in water hinder its clinical application. Biotransformation of celastrol using either whole cells or purified enzymes to form less toxi...

Pattern recognition has been widely used in various applications of image processing. It is used to extract meaningful image features from the given image samples and to build classification systems with the intelligence of human recognition. Convolutional Neural Network (CNN) [1] has been one of the most popular and widely used methods for image p...

Background/purpose Metabolites in blood have been found associated with the occurrence of vascular diseases, but its role in the functional recovery of stroke is unclear. The aim of this study is to investigate whether the untargeted metabolomics at the acute stage of ischemic stroke is able to predict functional recovery. Methods One hundred and...

The capability of gut microbiota in degrading foods and drugs administered orally can result in diversified efficacies and toxicity interpersonally and cause significant impact on human health. Production of atherogenic trimethylamine N-oxide (TMAO) from carnitine is a gut microbiota-directed pathway and varies widely among individuals. Here we dem...

The capability of gut microbiota in degrading foods and drugs administered orally can result in diversified efficacies and toxicity interpersonally and cause significant impact on human health. Production of atherogenic trimethylamine N-oxide (TMAO) from carnitine is a gut microbiota-directed pathway and varies widely among individuals. Here we dem...

Background We developed and validated an artificial intelligence (AI)-assisted prediction of preeclampsia applied to a nationwide health insurance dataset in Indonesia. Methods The BPJS Kesehatan dataset have been preprocessed using a nested case-control design into preeclampsia/eclampsia (n = 3318) and normotensive pregnant women (n = 19,883) fro...

Background: Preeclampsia and intrauterine growth restriction are placental dysfunction-related disorders (PDDs) that require a referral decision be made within a certain time period. An appropriate prediction model should be developed for these diseases. However, previous models did not demonstrate robust performances and/or they were developed fr...

Morphine is a strong painkiller acting through mu opioid receptor (MOR). Full-length 7-transmembrane (TM) variants of MOR share similar amino acid sequences of TM domains in rodents and humans; however, interspecies differences in N- and C-terminal amino acid sequences of MOR splice variants dramatically affect the downstream signaling. Thus, it is...

Strain GA A07 was identified as an intestinal Bacillus bacterium of zebrafish, which has high efficiency to biotransform the triterpenoid, ganoderic acid A (GAA), into GAA-15-O-β-glucoside. To date, only two known enzymes (BsUGT398 and BsUGT489) of Bacillus subtilis ATCC 6633 strain can biotransform GAA. It is thus worthwhile to identify the respon...

BACKGROUND Predictions in pregnancy care are complex because of interactions among multiple factors. Hence, pregnancy outcomes are not easily predicted by a single predictor using only one algorithm or modeling method. OBJECTIVE This study aims to review and compare the predictive performances between logistic regression (LR) and other machine lea...

Ganoderic acid A (GAA) is a bioactive triterpenoid isolated from the medicinal fungus Ganoderma lucidum. Our previous study showed that the Bacillus subtilis ATCC (American type culture collection) 6633 strain could biotransform GAA into compound (1), GAA-15-O-β-glucoside, and compound (2). Even though we identified two glycosyltransferases (GT) to...

Polyhydroxybutyrate (PHB) is biodegradable and renewable and thus considered as a promising alternative to petroleum-based plastics. However, PHB production is costly due to expensive carbon sources for culturing PHB-accumulating microorganisms under sterile conditions. We discovered a hyper PHB-accumulating denitrifying bacterium, Zobellella denit...

BACKGROUND Preeclampsia and intrauterine growth restriction are placental dysfunction–related disorders (PDDs) that require a referral decision be made within a certain time period. An appropriate prediction model should be developed for these diseases. However, previous models did not demonstrate robust performances and/or they were developed from...

Plasmidomes have been typically studied in environments abundant in bacteria, and this is the first study to explore plasmids from an environment characterized by low cell density. We specifically target groundwater, a significant source of water for human/agriculture use. We used samples from a well-studied site and identified hundreds of circular...

We present reference-quality genome assembly and annotation for the stout camphor tree (Cinnamomum kanehirae (Laurales, Lauraceae)), the first sequenced member of the Magnoliidae comprising four orders (Laurales, Magnoliales, Canellales and Piperales) and over 9,000 species. Phylogenomic analysis of 13 representative seed plant genomes indicates th...

Background Endolithic microbes in coral skeletons are known to be a nutrient source for the coral host. In addition to aerobic endolithic algae and Cyanobacteria, which are usually described in the various corals and form a green layer beneath coral tissues, the anaerobic photoautotrophic green sulfur bacteria (GSB) Prosthecochloris is dominant in...

Background Endolithic microbes in coral skeletons are known to be a nutrient source for the coral host. In addition to aerobic endolithic algae and Cyanobacteria, which are usually described in the various corals and form a green layer beneath coral tissues, the anaerobic photoautotrophic green sulfur bacteria (GSB) Prosthecochloris is dominant in...

Steroids are ubiquitous and abundant natural compounds that display recalcitrance. Biodegradation via sludge communities in wastewater treatment plants is the primary removal process for steroids. To date, compared to studies for aerobic steroid degradation, the knowledge of anaerobic degradation of steroids has been based on only a few model organ...