scholarly article | Q13442814 |
P8978 | DBLP publication ID | journals/jcheminf/LampaAS16 |
P6179 | Dimensions Publication ID | 1024308776 |
P356 | DOI | 10.1186/S13321-016-0179-6 |
P2888 | exact match | https://scigraph.springernature.com/pub.10.1186/s13321-016-0179-6 |
P932 | PMC publication ID | 5123367 |
P698 | PubMed publication ID | 27942268 |
P50 | author | Ola Spjuth | Q27061853 |
Jonathan Alvarsson | Q28865170 | ||
Samuel Lampa | Q30046332 | ||
P2860 | cites work | Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences | Q21092859 |
QSAR investigation of NaV1.7 active compounds using the SVM/Signature approach and the Bioclipse Modeling platform. | Q51297382 | ||
Notable design patterns for domain-specific languages | Q56335155 | ||
SLURM: Simple Linux Utility for Resource Management | Q59447200 | ||
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Large-scale ligand-based predictive modelling using support vector machines | Q27902338 | ||
Galaxy: a web-based genome analysis tool for experimentalists | Q28270252 | ||
A review of bioinformatic pipeline frameworks | Q28916344 | ||
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Drug discovery applications for KNIME: an open source data mining platform | Q30575364 | ||
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Ruffus: a lightweight Python library for computational pipelines | Q33694223 | ||
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Snakemake--a scalable bioinformatics workflow engine | Q34386337 | ||
BioBlend: automating pipeline analyses within Galaxy and CloudMan | Q34695213 | ||
Yabi: An online research environment for grid, high performance and cloud computing | Q35818548 | ||
Exploiting QSAR models in lead optimization. | Q37207162 | ||
Toward a class-independent quantitative structure--activity relationship model for uncouplers of oxidative phosphorylation | Q40111526 | ||
Ligand-based target prediction with signature fingerprints | Q42683682 | ||
Comparing Text-based and Graphic User Interfaces for novice and expert users. | Q43162697 | ||
Application of advanced in silico methods for predictive modeling and information integration | Q44233105 | ||
Benchmarking study of parameter variation when using signature fingerprints together with support vector machines | Q44978924 | ||
The signature molecular descriptor. 1. Using extended valence sequences in QSAR and QSPR studies | Q46633192 | ||
P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
P6216 | copyright status | copyrighted | Q50423863 |
P4510 | describes a project that uses | Jupyter notebook file | Q70357595 |
P921 | main subject | drug discovery | Q1418791 |
P304 | page(s) | 67 | |
P577 | publication date | 2016-11-24 | |
P1433 | published in | Journal of Cheminformatics | Q6294930 |
P1476 | title | Towards agile large-scale predictive modelling in drug discovery with flow-based programming design principles | |
P478 | volume | 8 |
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Q94530861 | MaRe: Processing Big Data with application containers on Apache Spark |
Q57278386 | PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud |
Q61660063 | PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud |
Q56699426 | SciPipe - A workflow library for agile development of complex and dynamic bioinformatics pipelines |
Q64085619 | SciPipe: A workflow library for agile development of complex and dynamic bioinformatics pipelines |
Q113312266 | SciPipe—Turning Scientific Workflows into Computer Programs |
Q94335553 | Towards reproducible computational drug discovery |
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