scholarly journals Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion

2021 ◽  
Author(s):  
Yuanqing Tang ◽  
Zhi Li ◽  
Mansoor Ani Najeeb Nellikkal ◽  
Hamed Eramian ◽  
Emory M. Chan ◽  
...  
Keyword(s):  
High Throughput ◽  
Model Fusion ◽  
Prediction Quality

scholarly journals Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding

MycoKeys ◽  
2018 ◽  
Vol 39 ◽  
pp. 29-40 ◽  
Author(s):  
Sten Anslan ◽  
R. Henrik Nilsson ◽  
Christian Wurzbacher ◽  
Petr Baldrian ◽  
Leho Tedersoo ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Computation Time ◽  
Potential Effect ◽  
Data Sets ◽  
Sequencing Data ◽  
Operational Taxonomic Units ◽  
High Throughput Sequencing Data ◽  
Recent Developments

Along with recent developments in high-throughput sequencing (HTS) technologies and thus fast accumulation of HTS data, there has been a growing need and interest for developing tools for HTS data processing and communication. In particular, a number of bioinformatics tools have been designed for analysing metabarcoding data, each with specific features, assumptions and outputs. To evaluate the potential effect of the application of different bioinformatics workflow on the results, we compared the performance of different analysis platforms on two contrasting high-throughput sequencing data sets. Our analysis revealed that the computation time, quality of error filtering and hence output of specific bioinformatics process largely depends on the platform used. Our results show that none of the bioinformatics workflows appears to perfectly filter out the accumulated errors and generate Operational Taxonomic Units, although PipeCraft, LotuS and PIPITS perform better than QIIME2 and Galaxy for the tested fungal amplicon dataset. We conclude that the output of each platform requires manual validation of the OTUs by examining the taxonomy assignment values.

scholarly journals Application of Bioactivity Profile Based Fingerprints for Building Machine Learning Models

2018 ◽  
Author(s):  
Noé Sturm ◽  
Jiangming Sun ◽  
Yves Vandriessche ◽  
Andreas Mayr ◽  
Günter Klambauer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
High Throughput ◽  
Scaffold Hopping ◽  
Learning Models ◽  
Industrial Data ◽  
Structural Descriptors ◽  
Bioactivity Profile ◽  
Machine Learning Models

<div>This article describes an application of high-throughput fingerprints (HTSFP) built upon industrial data accumulated over the years. </div><div>The fingerprint was used to build machine learning models (multi-task deep learning + SVM) for compound activity predictions towards a panel of 131 targets. </div><div>Quality of the predictions and the scaffold hopping potential of the HTSFP were systematically compared to traditional structural descriptors ECFP. </div><div><br></div>

scholarly journals Improving prediction quality of sea surface temperature (SST) in Niño3.4 region using Bayesian Model Averaging

2021 ◽  
Vol 893 (1) ◽  
pp. 012028
Author(s):  
Robi Muharsyah ◽  
Dian Nur Ratri ◽  
Damiana Fitria Kussatiti
Keyword(s):  
Surface Temperature ◽  
Bayesian Model ◽  
Bayesian Model Averaging ◽  
Model Averaging ◽  
Seasonal Forecast ◽  
Sea Surface ◽  
Post Processing ◽  
Enso Events ◽  
Prediction Quality

Abstract Prediction of Sea Surface Temperature (SST) in Niño3.4 region (170 W - 120 W; 5S - 5N) is important as a valuable indicator to identify El Niño Southern Oscillation (ENSO), i.e., El Niño, La Niña, and Neutral condition for coming months. More accurate prediction Niño3.4 SST can be used to determine the response of ENSO phenomenon to rainfall over Indonesia region. SST predictions are routinely released by meteorological institutions such as the European Center for Medium-Range Weather Forecasts (ECMWF). However, SST predictions from the direct output (RAW) of global models such as ECMWF seasonal forecast is suffering from bias that affects the poor quality of SST predictions. As a result, it also increases the potential errors in predicting the ENSO events. This study uses SST from the output Ensemble Prediction System (EPS) of ECMWF seasonal forecast, namely SEAS5. SEAS5 SST is downloaded from The Copernicus Climate Change Service (C3S) for period 1993-2020. One value representing SST over Niño3.4 region is calculated for each lead-time (LT), LT0-LT6. Bayesian Model Averaging (BMA) is selected as one of the post-processing methods to improve the prediction quality of SEAS5-RAW. The advantage of BMA over other post-processing methods is its ability to quantify the uncertainty in EPS, which is expressed as probability density function (PDF) predictive. It was found that the BMA calibration process reaches optimal performance using 160 months training window. The result show, prediction quality of Niño3.4 SST of BMA output is superior to SEAS5-RAW, especially for LT0, LT1, and LT2. In term deterministic prediction, BMA shows a lower Root Mean Square Error (RMSE), higher Proportion of Correct (PC). In term probabilistic prediction, the error rate of BMA, which is showed by the Brier Score is lower than RAW. Moreover, BMA shows a good ability to discriminating ENSO events which indicates by AUC ROC close to a perfect score.

Increasing the Prediction Quality of Software Defective Modules with Automatic Feature Engineering

2018 ◽  
pp. 527-535
Author(s):  
Alexandre Moreira Nascimento ◽  
Vinícius Veloso de Melo ◽  
Luiz Alberto Vieira Dias ◽  
Adilson Marques da Cunha
Keyword(s):  
Feature Engineering ◽  
Prediction Quality

High Throughput SNP Genotyping with Two Mini-sequencing Assays

2004 ◽  
Vol 36 (6) ◽  
pp. 379-384 ◽  
Author(s):  
Chunqing Luo ◽  
Libin Deng ◽  
Changqing Zeng ◽  
You-Xin Jin
Keyword(s):  
High Throughput ◽  
Snp Genotyping ◽  
Success Rates ◽  
Ionization Time ◽  
Data Process ◽  
Pcr Product ◽  
Human Chromosome 3 ◽  
Pcr Technology ◽  
The Cost

Abstract Two mini-sequencing methods, FP-TDI (template-directed dye-terminator incorporation with fluorescence-polarization) and MassArray (matrix assisted laser desorption ionization time of flight detection mass spectrometry), were optimized. A numeric standard was introduced to evaluate the SNP scoring quality of FP-TDI assay, thus made the optimization work easier. At the same time, using multi-PCR technology, 8-plex genotyping of MassArray assay was successfully carried out, some softwares were developed and the data process of MassArray was highly automated. Then these two methods were applied to high throughput SNP genotyping, the accuracy, efficiency and robustness were compared. The result shows FP-TDI is more sensitive to the concentration of SNPprimer and PCR product, as well as extension cycles, the SNPprimer length of FP-TDI should be 24–30 bp long, whereas MassArray assay prefers to be as short as only 16 bp. Altogether 6440 SNP sites of human chromosome 3 were genotyped in a sample of 90 individuals, 4792 sites by FP-TDI assay and 1648 sites by MassArray assay, the success rates of FP-TDI and MassArray were 67.7% and 93.6% respectively. The throughput of MassArray was higher than FP-TDI, and the cost of MassArray was lower, MassArray was more suitable for high throughput SNP genotyping.

scholarly journals High-throughput DNA barcoding of oligochaetes for abundance-based indices to assess the biological quality of sediments in streams and lakes

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Régis Vivien ◽  
Laure Apothéloz-Perret-Gentil ◽  
Jan Pawlowski ◽  
Inge Werner ◽  
Michel Lafont ◽  
...  
Keyword(s):  
Dna Barcoding ◽  
High Throughput ◽  
Biological Quality

scholarly journals Stability of Screening Compounds in Wet DMSO

2008 ◽  
Vol 13 (10) ◽  
pp. 999-1006 ◽  
Author(s):  
Caroline Engeloch ◽  
Ulrich Schopfer ◽  
Ingo Muckenschnabel ◽  
Francois Le Goff ◽  
Hervé Mees ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Medicinal Chemistry ◽  
Storage Conditions ◽  
Pragmatic Approach ◽  
Analytical Quality ◽  
The Past ◽  
Effect Of Water ◽  
The Impact

The impact of storage conditions on compound stability and compound solubility has been debated intensely over the past 5 years. At Novartis, the authors decided to opt for a storage concept that can be considered controversial because they are using a DMSO/water (90/10) mixture as standard solvent. To assess the effect of water in DMSO stocks on compound stability, the authors monitored the purity of a subset of 1404 compounds from ongoing medicinal chemistry projects over several months. The study demonstrated that 85% of the compounds were stable in wet DMSO over a 2-year period at 4 °C. This result validates the storage concept developed at Novartis as a pragmatic approach that takes advantage of the benefits of DMSO/water mixtures while mediating the disadvantages. In addition, the authors describe how purity data collected over the course of the chemical validation of high-throughput screening actives are used to improve the analytical quality of the Novartis screening deck. ( Journal of Biomolecular Screening 2008:999-1006)

scholarly journals The importance of triaging in determining the quality of output from high-throughput screening

2015 ◽  
Vol 7 (14) ◽  
pp. 1847-1852 ◽  
Author(s):  
Philip Jones ◽  
Stuart McElroy ◽  
Angus Morrison ◽  
Andrew Pannifer
Keyword(s):  
High Throughput ◽  
High Throughput Screening

scholarly journals Glycated Haemoglobin: An Assessment of High Capacity Liquid Chromatographic and Immunoassay Methods

1992 ◽  
Vol 29 (5) ◽  
pp. 494-505 ◽  
Author(s):  
Susan J Standing ◽  
Richard P Taylor
Keyword(s):  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
High Throughput ◽  
High Performance ◽  
High Capacity ◽  
Glycated Haemoglobin ◽  
Coefficients Of Variation ◽  
Operation Flexibility ◽  
Liquid Chromatographic

We have assessed five high-throughput systems for the measurement of glycated haemoglobin and have reviewed published evaluations of individual analysers. All systems offered better precision than a widely used electroendosmosis method. The low pressure chromatography and immunoassay systems demonstrated greater between-batch imprecision than the high performance liquid chromatography analysers, the latter achieving the proposed analytical goal of between-batch coefficients of variation less than 5%. Agreement between all systems measuring HbA1 was good but there was variability amongst observed HbA1c values. The systems were also assessed for their quality of chromatographic separation, simplicity of operation, flexibility, cost and potential for interference by other haemoglobins.

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