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  1. 4121
    “…The study demonstrates the suitability of SPIND for indexing sparse inorganic crystal data with smaller unit cells, and for improving the quality of serial femtosecond protein crystallography data, significantly reducing the amount of sample and beam time required by making better use of limited data sets. SPIND is written in Python and is publicly available under the GNU General Public License from https://github.com/LiuLab-CSRC/SPIND.…”
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    SPIND: a reference-based auto-indexing algorithm for sparse serial crystallography data
  2. 4122
    “…Our implementation is compatible with multiple protein design frameworks and is freely available as a set of python scripts (https://github.com/JiangTian/adaptive-geometric-search-for-protein-design).…”
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    An adaptive geometric search algorithm for macromolecular scaffold selection
  3. 4123
    “…Here, we present CRIS.py, a simple and highly versatile python-based program which concurrently analyzes next-generation sequencing data for both knock-out and multiple user-specified knock-in modifications from one or many edited samples. …”
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    CRIS.py: A Versatile and High-throughput Analysis Program for CRISPR-based Genome Editing
  4. 4124
    “…We present Stytra, a flexible, open-source software package, written in Python and designed to cover all the general requirements involved in larval zebrafish behavioral experiments. …”
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    Stytra: An open-source, integrated system for stimulation, tracking and closed-loop behavioral experiments
  5. 4125
    por Watts, Stephen C., Holt, Kathryn E.
    Publicado 2019
    “…Here we present hicap, a software tool for rapid in silico serotype prediction from H. influenzae genome sequences. hicap is written using Python3 and is freely available at https://github.com/scwatts/hicap under the GNU General Public License v3 (GPL3). …”
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    hicap: In Silico Serotyping of the Haemophilus influenzae Capsule Locus
  6. 4126
    “…By providing direct access via the web-interface as well as a Python API, we seek to accelerate the discovery of catalytic materials for sustainable energy applications by enabling researchers to efficiently use the data as a basis for new calculations and model generation.…”
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    Catalysis-Hub.org, an open electronic structure database for surface reactions
  7. 4127
    “…AVAILABILITY AND IMPLEMENTATION: SJARACNe is implemented in C++ (computational core) and Python (pipelining scripting wrapper, ≥3.6.1). It is freely available at https://github.com/jyyulab/SJARACNe. …”
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    SJARACNe: a scalable software tool for gene network reverse engineering from big data
  8. 4128
    “…RESULTS: Here, we present circtools, a modular, Python-based framework for computational circRNA analyses. …”
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    circtools—a one-stop software solution for circular RNA research
  9. 4129
    “…AVAILABILITY AND IMPLEMENTATION: CAARS is implemented in Python and Ocaml and is freely available at https://github.com/carinerey/caars. …”
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    CAARS: comparative assembly and annotation of RNA-Seq data
  10. 4130
    “…AVAILABILITY AND IMPLEMENTATION: Block HSIC Lasso is implemented in the Python 2/3 package pyHSICLasso, available on PyPI. …”
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    Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data
  11. 4131
    “…AVAILABILITY AND IMPLEMENTATION: COPAL is written in python and is available from http://github.com/cmbi/copal. …”
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    COmplexome Profiling ALignment (COPAL) reveals remodeling of mitochondrial protein complexes in Barth syndrome
  12. 4132
    “…AVAILABILITY AND IMPLEMENTATION: We created the ‘dphmix’ Python package: https://pypi.org/project/dphmix/. …”
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    Variational infinite heterogeneous mixture model for semi-supervised clustering of heart enhancers
  13. 4133
    “…The microcomputer was programmed in Python language to capture time-lapse images and videos. …”
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    Facile assembly of an affordable miniature multicolor fluorescence microscope made of 3D-printed parts enables detection of single cells
  14. 4134
    por Roads, Brett D., Mozer, Michael C.
    Publicado 2019
    “…The relevant tools are available as the Python package PsiZ, which can be cloned from GitHub (https://github.com/roads/psiz).…”
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    Obtaining psychological embeddings through joint kernel and metric learning
  15. 4135
    “…Here, we document the Transitivity code, written in Python, a free open-source code compatible with Windows, Linux and macOS platforms. …”
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    “Transitivity”: A Code for Computing Kinetic and Related Parameters in Chemical Transformations and Transport Phenomena
  16. 4136
    “…Our research made use of the scikit-learn library for the Python programming language and functions for regression analysis built into the Microsoft Excel software. …”
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    Forecasting the Prevalence of Diabetes Mellitus Using Econometric Models
  17. 4137
    “…AVAILABILITY AND IMPLEMENTATION: OncodriveCLUSTL is available as an installable Python 3.5 package. The source code and running examples are freely available at https://bitbucket.org/bbglab/oncodriveclustl under GNU Affero General Public License. …”
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    OncodriveCLUSTL: a sequence-based clustering method to identify cancer drivers
  18. 4138
    “…AVAILABILITY AND IMPLEMENTATION: DISPOT is implemented in Python 2.7 and packaged as an open-source tool. DISPOT is implemented in two modes, basic and auto-extraction. …”
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    DISPOT: a simple knowledge-based protein domain interaction statistical potential
  19. 4139
    “…In this context, using the rationale behind classical secretion of proteins through the secretory pathway, a Python tool capable of predicting classically secreted proteins was developed. …”
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    In silico approach to predict pancreatic β-cells classically secreted proteins
  20. 4140
    “…Rate of learning, programming accuracy, and post-test declarative knowledge were used as outcome measures in 36 individuals who participated in ten 45-minute Python training sessions. The resulting models explained 50–72% of the variance in learning outcomes, with language aptitude measures explaining significant variance in each outcome even when the other factors competed for variance. …”
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    Relating Natural Language Aptitude to Individual Differences in Learning Programming Languages
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