12 papers · ranked by Valyu relevance
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…
Miaoshan Lu, Hengxuan Jiang, Ruimin Wang, Shaowei An + 2 more
Plate Design is a necessary and time-consuming operation for GC/LC-MS based sample preparation. The implementation of the inter-batch balancing algorithm and the intra-batch randomization algorithm can have a significant impact on the final analysis results. For researchers without programming skills, a stable and…
Grant Ongo, Sébastien G. Ricoult, Timothy E. Kennedy, David Juncker
Cell navigation is directed by inhomogeneous distributions of extracellular cues. It is well known that noise plays a key role in biology and is present in naturally occurring gradients at the micro- and nanoscale, yet it has not been studied with gradients in vitro. Here, we introduce novel algorithms to produce…
Dogan Corus, Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre
Understanding how the time-complexity of evolutionary algorithms (EAs) depend on their parameter settings and characteristics of fitness landscapes is a fundamental problem in evolutionary computation. Most rigorous results were derived using a handful of key analytic techniques, including drift analysis. However…
Arjun Chandrasekhar, Deborah M. Gordon, Saket Navlakha
We study how the arboreal turtle ant (Cephalotes goniodontus) solves a fundamental computing problem: maintaining a trail network and finding alternative paths to route around broken links in the network. Turtle ants form a routing backbone of foraging trails linking several nests together. This species travels only in…
Tung Dang, Hirohisa Kishino
Random forest (RF) captures complex feature patterns that differentiate groups of samples and is rapidly being adopted in microbiome studies. However, a major challenge is the high dimensionality of microbiome datasets. They include thousands of species or molecular functions of particular biological interest. This…
Prasad U. Bandodkar, Razeen R. Shaikh, Gregory T. Reeves
Model development is essential to gain a mathematical understanding of the underlying phenomena in systems biology. In most models, it is typically hard to estimate the values of the biophysical/phenomenological parameters that characterize the model. The parameters are estimated by minimizing a function that reduces a…
Dileep Kishore, Srikiran Chandrasekaran
Biological systems are intrinsically noisy and this noise may determine the qualitative outcome of the system. In the absence of analytical solutions to mathematical models incorporating noise, stochastic simulation algorithms are useful to explore the possible trajectories of these systems. Algorithms used for such…
Changin Oh, Kathleen P. Wilkie
We present the Toroidal Search Algorithm (TSA), a novel population-based metaheuristic optimization method inspired by the topology of a torus. Conventional metaheuristics frequently suffer from boundary stagnation, a phenomenon that severely degrades performance in bounded and high-dimensional search spaces. TSA…
Juan P. Franco, Karlo Doroc, Nitin Yadav, Peter Bossaerts + 1 more
The survival of human organisms depends on our ability to solve complex tasks in the face of limited cognitive resources. However, little is known about the factors that drive the complexity of those tasks. Here, building on insights from computational complexity theory, we quantify the computational hardness of…
Joshua Kaminsky, Lindsay T. Keegan, C. Jessica E. Metcalf, Justin Lessler
Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervetnion, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the…
Kagari Yamada, Kazushi Tsutsui, Kazutoshi Kudo
Human intuition about randomness is systematically biased. When asked to generate random sequences, people systematically generate too many alternations. At the same time, game-theoretic analyses of competitive interactions prescribe truly random mixed strategies as the unique way to remain unpredictable to an…