mmpdb: An Open Source Matched Molecular Pair Platform for Large Multi-Property Datasets

2018 ◽  
Author(s):  
Andrew Dalke ◽  
Jerome Hert ◽  
Christian Kramer
Keyword(s):  
Open Source ◽  
Large Datasets ◽  
Molecular Pair ◽  
New Algorithms

We present mmpdb, an open source Matched Molecular Pair (MMP) platform to create, compile, store, retrieve, and use MMP rules. mmpdb is suitable for the large datasets typically found in pharmaceutical and agrochemical companies and provides new algorithms for fragment canonicalization and stereochemistry handling. The platform is written in Python and based on the RDKit toolkit. mmpdb is freely available.

scholarly journals mmpdb: An Open Source Matched Molecular Pair Platform for Large Multi-Property Datasets

2018 ◽  
Author(s):  
Andrew Dalke ◽  
Jerome Hert ◽  
Christian Kramer
Keyword(s):  
Open Source ◽  
Large Datasets ◽  
Molecular Pair ◽  
New Algorithms

We present mmpdb, an open source Matched Molecular Pair (MMP) platform to create, compile, store, retrieve, and use MMP rules. mmpdb is suitable for the large datasets typically found in pharmaceutical and agrochemical companies and provides new algorithms for fragment canonicalization and stereochemistry handling. The platform is written in Python and based on the RDKit toolkit. mmpdb is freely available.

scholarly journals mixl: An open-source R package for estimating complex choice models on large datasets

2021 ◽  
Vol 39 ◽  
pp. 100284
Author(s):  
Joseph Molloy ◽  
Felix Becker ◽  
Basil Schmid ◽  
Kay W. Axhausen
Keyword(s):  
Open Source ◽  
R Package ◽  
Choice Models ◽  
Large Datasets

scholarly journals Real Time Object Detection Canbe Embedded on Low Powered Devices

2019 ◽  
Author(s):  
Jimut Bahan Pal
Keyword(s):  
Neural Networks ◽  
Object Detection ◽  
Open Source ◽  
Real Time ◽  
Detection System ◽  
Computing Power ◽  
Convolution Neural Networks ◽  
Real Challenge ◽  
New Algorithms

It has been a real challenge for computers with low computing power and memory to detect objects in real time. After the invention of Convolution Neural Networks (CNN) it is easy for computers to detect images and recognize them. There are several technologies and models which can detect objects in real time, but most of them require high end technologies in terms of GPUs and TPUs. Though, recently many new algorithms and models have been proposed, which runs on low resources. In this paper we studied MobileNets to detect objects using webcam to successfully build a real time objectdetection system. We observed the pre trained model of the famous MS COCO dataset to achieve our purpose. Moreover, we applied Google’s open source TensorFlow as our back end. This real time object detection system may help in future to solve various complex vision problems.

scholarly journals OSPREY 3.0: Open-Source Protein Redesign for You, with Powerful New Features

2018 ◽  
Author(s):  
Mark A. Hallen ◽  
Jeffrey W. Martin ◽  
Adegoke Ojewole ◽  
Jonathan D. Jou ◽  
Anna U. Lowegard ◽  
...  
Keyword(s):  
Protein Binding ◽  
Open Source ◽  
Protein Design ◽  
Open Source Software ◽  
Ease Of Use ◽  
Biophysical Modeling ◽  
Order Of Magnitude ◽  
Design Software ◽  
Protein Redesign ◽  
New Algorithms

We present OSPREY 3.0, a new and greatly improved release of the OSPREY protein design software. OSPREY 3.0 features a convenient new Python interface, which greatly improves its ease of use. It is over two orders of magnitude faster than previous versions of OSPREY when running the same algorithms on the same hardware. Moreover, OSPREY 3.0 includes several new algorithms, which introduce substantial speedups as well as improved biophysical modeling. It also includes GPU support, which provides an additional speedup of over an order of magnitude. Like previous versions of OSPREY, OSPREY 3.0 offers a unique package of advantages over other design software, including provable design algorithms that account for continuous flexibility during design and model conformational entropy. Finally, we show here empirically that OSPREY 3.0 accurately predicts the effect of mutations on protein-protein binding. OSPREY 3.0 is available at http://www.cs.duke.edu/donaldlab/osprey.php as free and open-source software.

Chiller

2021 ◽  
Vol 50 (1) ◽  
pp. 14-14
Author(s):  
Alan D. Fekete
Keyword(s):  
Open Source ◽  
Performance Characteristics ◽  
Transaction Management ◽  
Important Research ◽  
Standard Set ◽  
Database Transactions ◽  
Process Database ◽  
System Designs ◽  
New Algorithms ◽  
The Way

Many computing researchers and practitioners may be surprised to find a "research highlight" which innovates on the way to process database transactions. Work in the early 1970s, by Turing winner Jim Gray and others, established a standard set of techniques for transaction management. These remain the basis of most commercial and open-source platforms [1], and they are still taught in university database classes. So why is important research still needed in this topic? The technology environment keeps evolving, and new performance characteristics mean that new algorithms and system designs become appropriate. This perspective will summarise the early work, and point to how the field has continued to progress.

scholarly journals Recursive MAGUS: Scalable and accurate multiple sequence alignment

2021 ◽  
Vol 17 (10) ◽  
pp. e1008950
Author(s):  
Vladimir Smirnov
Keyword(s):  
Open Source ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
State Of The Art ◽  
Sequence Data ◽  
Large Datasets ◽  
Alignment Accuracy ◽  
Multiple Sequence ◽  
Large Numbers ◽  
Source Form

Multiple sequence alignment tools struggle to keep pace with rapidly growing sequence data, as few methods can handle large datasets while maintaining alignment accuracy. We recently introduced MAGUS, a new state-of-the-art method for aligning large numbers of sequences. In this paper, we present a comprehensive set of enhancements that allow MAGUS to align vastly larger datasets with greater speed. We compare MAGUS to other leading alignment methods on datasets of up to one million sequences. Our results demonstrate the advantages of MAGUS over other alignment software in both accuracy and speed. MAGUS is freely available in open-source form at https://github.com/vlasmirnov/MAGUS.

scholarly journals Open Source Web Software Architectures for Geo-graphic Information Systems: A Systematic Mapping Study

2018 ◽  
Vol 1 (2) ◽  
pp. 192
Author(s):  
Alvaro Uyaguari ◽  
Edison Espinosa-Gallardo ◽  
Milton Escobar-Sánchez ◽  
José Luis Carrillo-Medina ◽  
Patricio Espinel
Keyword(s):  
Information Systems ◽  
Software Architecture ◽  
Open Source ◽  
Geographic Information ◽  
Software Architectures ◽  
Systematic Mapping Study ◽  
Mapping Study ◽  
New Methods ◽  
Graphic Information ◽  
New Algorithms

Abstract. A geographic information system is an organized integration of hardware, software and geographic data designed to collect, store, manipulate, analyze and present geographically referenced information. In the development of applications web the software architecture are very important aspect when developing complex software efficiently. This research shows a mapping study which objective is know the state of the art of the software architectures of the geographic information systems for open source web environments. The results show that 74.19% of contributions are integrations of existing open source components, 16.13% add tools to the software architecture, and 9.68% integrate new methods to solve or improve algorithms that are part of the architecture. This indicates that further research is needed to experience new tools and/or new algorithms to solve or improve existing ones.

scholarly journals Single-Cell Virtual Cytometer allows user-friendly and versatile analysis and visualization of multimodal single cell RNAseq datasets

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Frédéric Pont ◽  
Marie Tosolini ◽  
Qing Gao ◽  
Marion Perrier ◽  
Miguel Madrid-Mencía ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Single Cell ◽  
Open Source ◽  
Open Source Software ◽  
Healthy Donor ◽  
Large Datasets ◽  
Integrated Analysis ◽  
Functional Maturation ◽  
User Friendly ◽  
Cell Data

Abstract The development of single-cell transcriptomic technologies yields large datasets comprising multimodal informations, such as transcriptomes and immunophenotypes. Despite the current explosion of methods for pre-processing and integrating multimodal single-cell data, there is currently no user-friendly software to display easily and simultaneously both immunophenotype and transcriptome-based UMAP/t-SNE plots from the pre-processed data. Here, we introduce Single-Cell Virtual Cytometer, an open-source software for flow cytometry-like visualization and exploration of pre-processed multi-omics single cell datasets. Using an original CITE-seq dataset of PBMC from an healthy donor, we illustrate its use for the integrated analysis of transcriptomes and epitopes of functional maturation in human peripheral T lymphocytes. So this free and open-source algorithm constitutes a unique resource for biologists seeking for a user-friendly analytic tool for multimodal single cell datasets.

scholarly journals SpaceHub: A high-performance gravity integration toolkit for few-body problems in astrophysics

2021 ◽  
Author(s):  
Yi-Han Wang ◽  
Nathan W C Leigh ◽  
Bin Liu ◽  
Rosalba Perna
Keyword(s):  
Open Source ◽  
High Performance ◽  
Error Control ◽  
Performance Accuracy ◽  
Eccentric Orbits ◽  
Planetary Dynamics ◽  
Arbitrary Precision ◽  
Accurate Computations ◽  
New Algorithms

Abstract We present the open source few-body gravity integration toolkit SpaceHub. SpaceHub offers a variety of algorithmic methods, including the unique algorithms AR-Radau, AR-Sym6, AR-ABITS and AR-chain+ which we show out-perform other methods in the literature and allow for fast, precise and accurate computations to deal with few-body problems ranging from interacting black holes to planetary dynamics. We show that AR-Sym6 and AR-chain+, with algorithmic regularization, chain algorithm, active round-off error compensation and a symplectic kernel implementation, are the fastest and most accurate algorithms to treat black hole dynamics with extreme mass ratios, extreme eccentricities and very close encounters. AR-Radau, the first regularized Radau integrator with round off error control down to 64 bits floating point machine precision, has the ability to handle extremely eccentric orbits and close approaches in long-term integrations. AR-ABITS, a bit efficient arbitrary precision method, achieves any precision with the least CPU cost compared to other open source arbitrary precision few-body codes. With the implementation of deep numerical and code optimization, these new algorithms in SpaceHub prove superior to other popular high precision few-body codes in terms of performance, accuracy and speed.

scholarly journals 3-D interactive visualisation tools for Hispectral line imaging

2016 ◽  
Vol 12 (S325) ◽  
pp. 305-310
Author(s):  
J. M. van der Hulst ◽  
D. Punzo ◽  
J. B. T. M. Roerdink
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Medical Image ◽  
Large Datasets ◽  
Qualitative And Quantitative ◽  
Comparative Modelling ◽  
Open Source Software Package ◽  
Automated Processing ◽  
Line Imaging ◽  
Interactive Visualisation

AbstractUpcoming HI surveys will deliver such large datasets that automated processing using the full 3-D information to find and characterize HI objects is unavoidable. Full 3-D visualization is an essential tool for enabling qualitative and quantitative inspection and analysis of the 3-D data, which is often complex in nature. Here we presentSlicerAstro, an open-source extension of3DSlicer, a multi-platform open source software package for visualization and medical image processing, which we developed for the inspection and analysis of HI spectral line data. We describe its initial capabilities, including 3-D filtering, 3-D selection and comparative modelling.

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