14 papers · ranked by Valyu relevance
Marek Wiewiórka, Agnieszka Szmurło, Paweł Stankiewicz, Tomasz Gambin
Pileup analysis is a building block of many bioinformatics pipelines, including variant calling and genotyping. This step tends to become a bottleneck of the entire assay since the straightforward pileup implementations involve processing of all base calls from all alignments sequentially. On the other hand, a…
Haotian Li
Machine learning and deep learning are novel and trending approaches to solving real-world scientific problems. Graph machine learning is dedicated to performing learning methods, such as graph neural networks, on non-Euclidean data such as graphs. Molecules, with their natural graph structures, could be analyzed by…
Peter G. Hawkins, Eli M. Swanson, Megan Feichtel
The size of individual single cell samples continues to grow with advancing technologies, as do the number of samples included in individual experiments and across organizations. This presents challenges for processing this data at scale, both in terms of computational throughput and the required size of the machines…
Jose L. Figueroa, Eliza Dhungel, Cory R. Brouwer, Richard Allen White
MetaCerberus is an exclusive HMM/HMMER-based tool that is massively parallel, on low memory, and provides rapid scalable annotation for functional gene inference across genomes to metacommunities. It provides robust enumeration of functional genes and pathways across many current public databases including KEGG (KO)…
Swier Garst, Julian Dekker, Marcel Reinders
Federated learning is an upcoming machine learning paradigm which allows data from multiple sources to be used for training of classifiers without the data leaving the source it originally resides. This can be highly valuable for use cases such as medical research, where gathering data at a central location can be…
Mengya Zhang, Qing Yu
Successful goal-directed behavior requires the maintenance and implementation of abstract task goals on concrete stimulus information in working memory. Previous working memory research has revealed distributed neural representations of task information across cortex. However, how the distributed task representations…
Patrick McKeever, Varun Mittal, Bryce Fukuda, Ka Yee Yeung + 1 more
The exponential growth of omics data requires novel strategies for storage, transfer, and processing of said data. We present a scheduler based on the Temporal.io workflow framework which enables two key optimizations of bioinformatics workflows. Firstly, we enable users to transparently map workflow steps to diverse…
Bishal Thapaliya, Riyasat Ohib, Eloy Geenjar, Jingyu Liu + 2 more
Recent advancements in neuroimaging have led to greater data sharing among the scientific community. However, institutions frequently maintain control over their data, citing concerns related to research culture, privacy, and accountability. This creates a demand for innovative tools capable of analyzing amalgamated…
Murukessan Perumal, M Srinivas
Medical data is not available for public access due to privacy concerns of the patients and the stakeholders’ trust-worthiness. However, Artificial Intelligence, especially all deeplearning models, is data-hungry and fails to produce clinically relevant results without much data. Moreover, augmentation strategies are…
Thomas R. Colin, Iris Ikink, Clay B. Holroyd
In natural and artificial neural networks, modularity and distributed structure afford complementary but competing benefits. The former allows for hierarchical representations that can flexibly recombine modules to address novel problems, whereas the latter affords better generalization. Here we investigate these…
Zvi Baratz, Yaniv Assaf
The goal of this article is to present “The Labbing Project”; a novel neuroimaging data aggregation and preprocessing web application built with Django and VueJS. Neuroimaging data can be complex and time-consuming to work with, especially for researchers with limited programming experience. This web application aims…
Lorea Alejaldre, Jesús Miró-Bueno, Angeles Hueso-Gil, Lewis Grozinger + 3 more
Genetic circuits confer computing abilities to living cells, performing novel transformations of input stimuli into output responses. These genetic circuits are routinely engineered for insertion into bacterial plasmids and chromosomes, using a design paradigm whose only spatial consideration is a linear ordering of…
Emmanouil Alexis, Sebastián Espinel-Ríos, Ioannis G. Kevrekidis, José L. Avalos
Designing dependable, self-regulated biochemical systems has long posed a challenge in the field of Synthetic Biology. Here, we propose a realization of a Proportional-Integral-Derivative-Acceleration (PIDA) control scheme as a Chemical Reaction Network (CRN) governed by mass action kinetics. A constituent element of…
Santiago Silva, Neil Oxtoby, Andre Altmann, Marco Lorenzi
In neuroimaging research, the utilization of multi-centric analyses is crucial for obtaining sufficient sample sizes and representative clinical populations. Data harmonization techniques are typically part of the pipeline in multi-centric studies to address systematic biases and ensure the comparability of the data.…