26 papers · ranked by Valyu relevance
Sebastian Bassi, Fran Lewitter
This article introduces the world of the Python computer language. It is assumed that readers have some previous programming experience in at least one computer language and are familiar with basic concepts such as data types, flow control, and functions. Python can be used to solve several problems that research…
Daniel Alabi, Joseph Ekpenyong, Alida Monaco
The NaijaCoder in-person summer camps are intensive programs for high school and pre-college students in Nigeria. The programs are meant to provide free instruction on the basics of algorithms and computer programming. In 2024, the camps were held in two locations within the country: (i) the Federal Capital Territory…
Berk Ekmekci, Charles E. McAnany, Cameron Mura, Francis Ouellette
Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware…
Berk Ekmekci, Charles E. McAnany, Cameron Mura
Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware…
Ian Stewart, Katherine A. Keith
Many scientific fields—including biology, health, education, and the social sciences—use machine learning (ML) to help them analyze data at an unprecedented scale. However, ML researchers who develop advanced methods rarely provide detailed tutorials showing how to apply these methods. Existing tutorials are often…
Dominique Sydow, Jaime Rodríguez-Guerra, Talia B. Kimber, David Schaller + 7 more
Computational pipelines have become a crucial part of modern drug discovery campaigns. Setting up and maintaining such pipelines, however, can be challenging and time-consuming --- especially for novice scientists in this domain. TeachOpenCADD is a platform that aims to teach domain-specific skills and to provide…
Heyuan Zeng, Jinbiao Zhang, Gabriel A. Preising, Tobias Rubel + 2 more
'Pramesh Singh' 'Anna Ritz'] Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed GRAPHERY, an interactive tutorial webserver that illustrates foundational graph…
Stephen Coshatt, He Yang, Shushan Wu, Jin Ye + 5 more
As machine learning and artificial intelligence are being integrated into cyber-physical systems, it is becoming important for engineers to know and understand these topics. In particular, sensor data is on the rise in these systems and therefore engineers need to understand which models are appropriate to time-series…
Gilderlanio Santana de Araújo
Teaching computer programming is not a simple task and it is challenging to introduce the concepts of programming in graduate programs of other fields. Little efforts have been made on engaging students in computational development after programming trainings. An emerging need is to establish subjects of bioinformatics…
Laura Mickes, Travis M. Seale-Carlisle, Xueqing Chen, Stewart Boogert
'Stewart Boogert'] pyWitness is a python toolkit for recognition memory experiments, with a focus on eyewitness identification (ID) data analysis and model fitting. The current practice is for researchers to use different statistical packages to analyze a single dataset. pyWitness streamlines the process. In addition…
Odd Petter Sand, Elise Lockwood, Marcos D. Caballero, Knut Mørken
We present here the lessons learned by iteratively designing a tutorial for first-year university students using computer programming to work with mathematical models. Alternating between design and implementation, we used video-taped task interviews and classroom observations to ensure that the design promoted student…
Anupam Ojha, Lane Votapka, Gary Huber, Shang Gao + 1 more
SEEKR2 (Simulation enabled estimation of kinetic rates v. 2) is a powerful and versatile software tool designed to computationally estimate the kinetics and thermodynamics of complex molecular processes, particularly emphasizing the process of receptor-ligand binding and unbinding. We present a suite of tutorials for…
Thomas Bartz–Beielstein
The goal of hyperparameter tuning (or hyperparameter optimization) is to optimize the hyperparameters to improve the performance of the machine or deep learning model. spotPython ("Sequential Parameter Optimization Toolbox in Python") is the Python version of the well-known hyperparameter tuner SPOT, which has been…
Anthony T. Bogetti, Jeremy M. G. Leung, John D. Russo, She Zhang + 11 more
We present six advanced tutorials instructing users in the best practices of using key new features and plugins/extensions of the WESTPA 2.0 software package, which consists of major upgrades for enabling applications of the weighted ensemble (WE) path sampling strategy to even larger systems and/or slower processes.…
Rohitash Chandra, Royce Chen, Joshua A. Simmons
Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain Monte-Carlo (MCMC) sampling methods are used to implement Bayesian inference. In the past three decades, MCMC sampling methods have…
Lucy Moctezuma, Lorena Benitez Rivera, Florentine van Nouhuijs, Faye Orcales + 4 more
This manuscript describes the development of a module that is part of a learning platform named “NIGMS Sandbox for Cloud-based Learning” https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers…
Rebecca Brunk, Kriti Shukla, Bryant Hutson, Yue Wang + 7 more
Genomic sequencing and other big biological data is unquestionably of paramount value, however the success in recruiting highly skilled individuals with diverse backgrounds has been limited. A main reason for this deficiency could be due to the lack of educational resources and early exposure to the field. With the…
Matteo De Matola, Giorgio Arcara
Convolutional neural networks (CNNs) are a class of artificial neural networks (ANNs). Since the early 2010s, they have been widely adopted as models of primate vision and classifiers of neuroimaging data, becoming relevant for a wealth of neuroscientific fields. However, the majority of neuroscience researchers come…
Knut Rand, Ivar Grytten, Milena Pavlovic, Chakravarthi Kanduri + 1 more
Python is a popular and widespread programming language for scientific computing, in large part due to the powerful array programming library NumPy, which makes it easy to write clean, vectorized and efficient code for handling large datasets. A challenge with using array programming for biological data is that the…
Martin Seifrid, Felix Strieth-Kalthoff, Mohammad Haddadnia, Tony Wu + 7 more
We introduce Chemspyd, a lightweight, open-source Python package for operating the popular laboratory robotic platforms from Chemspeed Technologies. As an add-on to the existing proprietary software suite, Chemspyd enables dynamic communication with the automated platform, laying the foundation for its modular…
Pattara Leelaprute, Bodin Chinthanet, Supatsara Wattanakriengkrai, Raula Gaikovina Kula + 2 more
'Raula Gaikovina Kula' 'Pongchai Jaisri' 'Takashi Ishio'] In the field of data science, and for academics in general, the Python programming language is a popular choice, mainly because of its libraries for storing, manipulating, and gaining insight from data. Evidence includes the versatile set of machine learning…
Authors not listed
With the rapid growth of chemical data and information, there is an increasing need for chemistry undergraduates to master Python tools for analyzing large chemical datasets and extracting key or feature information. Currently, more than 100,000 types of metal-organic frameworks (MOFs), as the material recently awarded…
Alex M. Ascension, Marcos J. Araúzo-Bravo
Big Data analysis is a discipline with a growing number of areas where huge amounts of data is extracted and analyzed. Parallelization in Python integrates Message Passing Interface via mpi4py module. Since mpi4py does not support parallelization of objects greater than 2^31^ bytes, we developed BigMPI4py, a Python…
Dimitar Georgiev, Simon Vilms Pedersen, Ruoxiao Xie, Álvaro Fernández-Galiana + 2 more
Raman spectroscopy is a non-destructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardisation, and the…
Hsuan-Ta Lin, Po-Ming Lee, Tzu-Chien Hsiao
Tutorial tactics are policies for an Intelligent Tutoring System (ITS) to decide the next action when there are multiple actions available. Recent research has demonstrated that when the learning contents were controlled so as to be the same, different tutorial tactics would make difference in students' learning gains.…
Authors not listed
Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…