Metallic glasses are frequently used as structural materials. Therefore, it is important to develop methods to predict their mechanical response as a function of the microstructure prior to loading. We develop a novel...
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Now in the era of big data, many are applying information methods accurately especially by social media. The aims of this study to classify the weather based on Twitter automatically using text mining by using Support...
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Now in the era of big data, many are applying information methods accurately especially by social media. The aims of this study to classify the weather based on Twitter automatically using text mining by using Support Vector Machine (SVM), MultinomialNaive Bayes (MNB), and Logistic Regression (LR) method. The experimental results show that SVM substantially outperforms various other machine learning algorithms for the task of text classification with an accuracy value of 93%. This result proves that SVM is very suitable for text categorization. We use clustering technique to read the pattern in customers’ opinion about the restaurant based on some measurement variables.
Twitter data provide rich and powerful information to leverage the dynamics of public perception to establish situational awareness and disaster mitigation strategies during critical times. In this paper, we perform t...
Twitter data provide rich and powerful information to leverage the dynamics of public perception to establish situational awareness and disaster mitigation strategies during critical times. In this paper, we perform topic modeling via Latent Dirichlet Allocation to extract topics from a collection of tweets related to Indonesia flood events in February 2021 with the query: “banjir”. The extracted topics are used as one of the features to build a generalized linear count time series model with Negative Binomial distribution. We find seven major topics from the model in which tweets containing a topic about the government’s role in handling the situation dominate the conversation. Taking into account a simple intervention analysis, we demonstrate a statistically significant change in the users’ behavior before and after the severe Jakarta flood on 20 February 2021. Moreover, a metric evaluation demonstrates that a covariate that describes the turning point of the Jakarta flood event is convenient to build a more accurate count time series model of the tweets.
Drug-Induced Liver Injury (DILI) is a major cause of failed drug candidates in clinical trials and withdrawal of approved drugs from the market. Therefore, machine learning-based DILI prediction can be key in increasi...
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ISBN:
(数字)9781728160344
ISBN:
(纸本)9781728160351
Drug-Induced Liver Injury (DILI) is a major cause of failed drug candidates in clinical trials and withdrawal of approved drugs from the market. Therefore, machine learning-based DILI prediction can be key in increasing the success rate of drug discovery because drug candidates that are predicted to potentially induce liver injury can be rejected before clinical trials. However, existing DILI prediction models mainly focus on the chemical structures of drugs. Since we cannot determine whether a drug will cause liver injury based solely on its structure, DILI prediction based on the transcriptional effect of a drug on a cell is necessary. In this paper, we propose GLIT which is a model that uses transcriptional response data and chemical structures and can be used for drug-induced liver injury prediction. GLIT learns the embedding vectors of drug structures and drug-induced gene expression profiles using graph attention networks in a biological knowledge graph for predicting DILI. GLIT outperformed a baseline model that uses only drug structure information by 7% and 19.2% in terms of correct classification rate (CCR) and Matthews correlation coefficient (MCC), respectively. In addition, we conducted a literature survey to confirm whether the class labels of drugs, in the unknown DILI class, predicted by GLIT are correct.
Numerous studies have investigated the differences and similarities between protein structures determined by solution NMR spectroscopy and those determined by x-ray crystallography. A fundamental question is whether a...
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Numerous studies have investigated the differences and similarities between protein structures determined by solution NMR spectroscopy and those determined by x-ray crystallography. A fundamental question is whether any observed differences are due to differing methodologies, or to differences in the behavior of proteins in solution versus in the crystalline state. Here, we compare the properties of the hydrophobic cores of high-resolution protein crystal structures and those in NMR structures, determined using increasing numbers and types of restraints. Prior studies have reported that many NMR structures have denser cores compared to those of high-resolution x-ray crystal structures. Our current work investigates this result in more detail, and finds that these NMR structures tend to violate basic features of protein stereochemistry, such as small non-bonded atomic overlaps and few Ramachandran and side chain dihedral angle outliers. We find that NMR structures solved with more restraints, and which do not significantly violate stereochemistry, have hydrophobic cores that have a similar size and packing fraction as their counterparts determined by x-ray crystallography at high-resolution. These results lead us to conclude that, at least regarding the core packing properties, high-quality structures determined by NMR and x-ray crystallography are the same, and the differences reported earlier are most likely a consequence of methodology, rather than fundamental differences between the protein in the two different environments. Significance: Dense packing of hydrophobic residues is key to protein structure and stability. Previously, it has been noted that structures solved by NMR spectroscopy have denser cores than x-ray crystal structures. Here, we calculate the core size and packing fraction of NMR structures with experimental restraints in the PDB. Their cores are typically smaller, but denser. However, NMR structures with accurate stereochemistry possess core pa
An incoherent feed-forward loop (IFFL) is a network motif known for its ability to accelerate responses and generate pulses. Though functions of IFFLs are well studied, most previous computational analysis of IFFLs us...
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Preservation of executive function, like inhibition, closely links to the quality of life in senior adults. Although neuroimaging literature has shown enhanced inhibitory function followed by aerobic exercise, current...
Preservation of executive function, like inhibition, closely links to the quality of life in senior adults. Although neuroimaging literature has shown enhanced inhibitory function followed by aerobic exercise, current evidence implies inconsistent neuroplasticity patterns along different time durations of exercise. Hence, we conducted a 12-week exercise intervention on 12 young and 14 senior volunteers and repeatedly measured the inhibitory functionality of distinct aspects (facilitation and interference effects) using the numerical Stroop task and functional Magnetic Resonance Imaging. Results showcased improved accuracy and reduced reaction times (RT) after 12-week exercise, attributed to frontoparietal and default mode network effects. In young adults, the first phase (0 to six weeks) exercise increased the activation of the right superior medial frontal gyrus, associated with reduced RT in interference, but in the second intervention phase (six to twelve weeks), the decreased activation of the left superior medial frontal gyrus positively correlated with reduced RT in facilitation. In senior adults, the first six-week intervention led to reduced activations of the inferior frontal gyrus, inferior parietal gyrus, and default mode network regions, associated with the reduced RT in interference. Still, in the second intervention phase, only the visual area exhibited increased activity, associated with reduced RT in interference. Except for the distinctive brain plasticity between the two phases of exercise intervention, the between-group comparison also presented that the old group gained more cognitive benefits within the first six weeks of exercise intervention;however, the cognitive improvements in the young group occurred after six weeks of intervention. Limited by the sample size, these preliminary findings corroborated the benefits of aerobic exercise on the inhibitory functions, implying an age × exercise interaction on the brain plasticity for both facilita
We conducted a thorough genome-wide investigation of protein phosphorylation in the halotolerant bacterium Mangrovibacter phragmitis (MPH) ASIOC01, using the Fe-IMAC enrichment method combined with tandem mass spectro...
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We conducted a thorough genome-wide investigation of protein phosphorylation in the halotolerant bacterium Mangrovibacter phragmitis (MPH) ASIOC01, using the Fe-IMAC enrichment method combined with tandem mass spectrometry under low- and high-salinity conditions. The phosphoproteome comprises 86 unique phosphorylated proteins, crucially involving pathways such as glycolysis/gluconeogenesis, the citrate cycle, chaperones, ribosomal proteins, and cell division. This study represents the first and most extensive investigation to-date comparing the bacterial phosphoproteome under different osmotic conditions using a gel-free approach. We identified 45 unique phosphoproteins in MPH cultured in media containing 1 % NaCl, and 33 exclusive phosphoproteins in MPH cultured in media containing 5 % NaCl. Eight phosphoproteins were detected in both growth conditions. Analysis of high-confidence phosphosites reveals that phosphorylation predominantly occurs on serine residues (52.3 %), followed by threonine (35.1 %) and tyrosine (12.6 %) residues. Interestingly, 34 % of the phosphopeptides display multiple phosphosites. Currently, prokaryotic phosphorylation site prediction platforms like MPSite and NetPhosBac 1.0 demonstrate an average prediction accuracy of only 21 % when applied to our dataset. Fourteen phosphoproteins did not yield matches when compared against dbPSP 2.0 (database of Phosphorylation Sites in Prokaryotes), indicating that these proteins may be novel phosphoproteins. These unique proteins undergoing phosphorylation under high salinity growth conditions potentially enhance their adaptive capabilities to environmental challenges.
Virtually all individuals aged 65 or older develop at least early pathology of Alzheimer's disease (AD), yet most lack disease-causing mutations in APP, PSEN, or MAPT, and many do not carry the APOE4 risk allele. ...
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Sugarcane plantations in Indonesia are still managed in a labor-intensive manner, especially plantation-owned by farmers. Labor intensive means that every stage of work in sugarcane plantation management still uses ma...
Sugarcane plantations in Indonesia are still managed in a labor-intensive manner, especially plantation-owned by farmers. Labor intensive means that every stage of work in sugarcane plantation management still uses manpower. One of the jobs in sugarcane plantations that requires a lot of labor is sugar cane harvesting. Trend changing in the workforce gender would affect the quantity and quality of jobs, which is determined by the workforce's capacity and the workload of the work performed. The result of this research was a sugarcane agricultural calculator that made it simple for farmers to measure manpower and transportation requirements in estimating harvest costs. Manpower and transportation of harvested sugarcane commodities were estimated through the workload approach, namely, crop production and manpower's ability to carry a load. These two components helped sugarcane farmers to determine manpower and transportation during the harvest. The final yield produced by the projected harvest labor cost would be known immediately.
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