26 papers · ranked by Valyu relevance
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…
Pohsun Feng, Ziqian Bi, Yizhu Wen, Benji Peng + 11 more
Language Models -- AutoML from Basics to State-of-the-Art Techniques Authors: ['Pohsun Feng' 'Ziqian Bi' 'Yizhu Wen' 'Benji Peng' 'Junyu Liu' 'Caitlyn Heqi Yin' 'Tianyang Wang' 'Keyu Chen' 'Sen Zhang' 'Ming Li' 'Jiawei Xu' 'Ming Liu' 'Xiaoyong Pan' 'Jinlang Wang' 'Qian Niu'] | 1 | Introduction to AutoML | | 13 | | ---…
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…
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…
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…
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…
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…
Gustavo Schiavone Crestana, Ubiratan da Silva Batista, Michelli Inácio Gonçalves Funnicelli, Larissa Graciano Braga + 9 more
The rapid evolution of high-throughput technologies in biosciences has generated diverse and voluminous datasets, requiring bioscientists to develop data manipulation and analysis skills. Python, known for its versatility and powerful libraries, has become a crucial tool for managing these datasets. However, there is a…
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…
Safoora Masoumi, Saeid Shahraz
Background Meta-analysis is a central method for quality evidence generation. In particular, meta-analysis is gaining speedy momentum in the growing world of quantitative information. There are several software applications to process and output expected results. Open-source software applications generating such…
Hongquan Bai, Xin Wang, Li Zhao
The rapid development of computers and technology affects modern daily life. Individuals in the digital age need to develop computational thinking (CT) skills. Existing studies have shown that programming teaching is conducive to cultivating students’ CT, and various learning models have different effects on the…
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…
Ali Arya
| 3 | Table of Content | | --- | --- | | Preface 8 | | | Notes 10 | | | 10 | Code Examples | | Signage and Numbering 11 | | | 12 | Chapter 1: Introduction | | 12 | 1.1. At the Restaurant | | 15 | 1.2. Algorithms | | 1.3. Programs 17 | | | 1.4. Programming and Algorithmic Thinking 21 | | | 25 | 1.5. Modularization | |…
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…
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…
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…
Vincent Noël, Aurélien Naldi, Laurence Calzone, Loic Paulevé + 1 more
This tutorial provides stepwise instructions to install the 20 tools integrated in the CoLoMoTo software suite, to develop reproducible dynamical analyses of logical models of complex biological molecular networks. The tutorial specifically focuses on the analysis of a previously published model of the regulatory…
Sterling G. Baird, Taylor D. Sparks
Title: Summary Learn how to build a Closed-loop Spectroscopy Lab: Light-mixing demo (CLSLab:Light) to perform color matching via RGB LEDs and a light sensor for under 100 USD and less than an hour of setup. Our tutorial covers ordering parts, verifying prerequisites, software setup, sensor mounting, testing, and an…
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…
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…
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…
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…