12 papers · ranked by Valyu relevance
Chaoming Wang, Xingsi Dong, Jiedong Jiang, Zilong Ji + 2 more
Whole-brain simulation stands as one of the most ambitious endeavors of our time, yet it remains constrained by significant technical challenges. A critical obstacle in this pursuit is the absence of a scalable online learning framework capable of supporting the efficient training of complex, diverse, and large-scale…
Mahmudur Rahman Hera, David Koslicki, Conrado Martínez
With the surge in sequencing data generated from an ever-expanding range of biological studies, designing scalable computational techniques has become essential. One effective strategy to enable large-scale computation is to split long DNA or protein sequences into k-mers, and summarize large k-mer sets into compact…
Ragnar Groot Koerkamp, Igor Martayan
Because of the rapidly-growing amount of sequencing data, computing sketches of large textual datasets has become an essential preprocessing task. These sketches are typically much smaller than the input sequences, but preserve sufficient information for downstream analysis. Minimizers are an especially popular…
Jamshed Khan, Laxman Dhulipala, Rob Patro
The rapid growth of genomic data over the past decade has made scalable and efficient sequence analysis algorithms, particularly for constructing de Bruijn graphs and their colored and compacted variants critical components of many bioinformatics pipelines. Colored compacted de Bruijn graphs condense repetitive…
Parashar Dhapola, Johan Rodhe, Rasmus Olofzon, Thomas Bonald + 3 more
The increasing capacity to perform large-scale single-cell genomic experiments continues to outpace the computational requirements to efficiently handle growing datasets. Herein we present Scarf, a modularly designed Python package that seamlessly interoperates with other single-cell toolkits and allows for…
J Kyle Medley, Shaik Asifullah, Joseph Hellerstein, Herbert M Sauro
Mechanistic kinetic models of biological pathways are an important tool for understanding biological systems. Constructing kinetic models requires fitting the parameters to experimental data. However, parameter fitting on these models is a non–convex, non–linear optimization problem. Many algorithms have been proposed…
Thomas Pirenne, Esther Florin
Estimating causal interactions between signals provides unique insights into their dynamics, and causal inference has been widely applied to electrophysiological data to elucidate brain communication. Multivariate autoregressive models (MVAR) form the basis of most causal estimation methods. However, the high…
Yuanchao Zhang, Deanne M. Taylor
In single-cell RNA-seq (scRNA-seq) experiments, the number of individual cells has increased exponentially due to significant improvements on single-cell isolation and massively parallel sequencing technologies. However, computational methods have not scaled to the same order, presenting analytical challenges to the…
Guohao Dou
We propose an algorithm to simulate Markovian SIS epidemics with homogeneous rates and pairwise interactions on a fixed undirected graph, assuming a distributed memory model of parallel programming and limited bandwidth. We offer an implementation of the algorithm in the form of pseudocode in the Appendix. Also, we…
Tizian Schulz, Paul Medvedev
Given a sequencing read, the broad goal of read mapping is to find the location(s) in the reference genome that have a “similar sequence”. Traditionally, “similar sequence” was defined as having a high alignment score and read mappers were viewed as heuristic solutions to this well-defined problem. For sketch-based…
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…
Benjamin Coleman, Benito Geordie, Li Chou, R. A. Leo Elworth + 2 more
The rise of whole-genome shotgun sequencing (WGS) has enabled numerous breakthroughs in large-scale comparative genomics research. However, the size of genomic datasets has grown exponentially over the last few years, leading to new challenges for traditional streaming algorithms. Modern petabyte-sized genomic datasets…