15 papers · ranked by Valyu relevance
Andre J. Aberer, Kassian Kobert, Alexandros Stamatakis
Modern sequencing technology now allows biologists to collect the entirety of molecular evidence for reconstructing evolutionary trees. We introduce a novel, user-friendly software package engineered for conducting state-of-the-art Bayesian tree inferences on data sets of arbitrary size. Our software introduces a…
Ivan Rodriguez-Conde, Celso Campos, Florentino Fdez-Riverola, Antonio Fernández-Caballero + 1 more
'Antonio Fernández-Caballero' 'Juan M. Corchado'] Motivated by the pervasiveness of artificial intelligence (AI) and the Internet of Things (IoT) in the current “smart everything” scenario, this article provides a comprehensive overview of the most recent research at the intersection of both domains, focusing on the…
Daniel E Schäffer, Samuel Sledzieski, Lenore Cowen, Bonnie Berger + 1 more
In the original D-SCRIPT implementation, inference proceeds serially: all protein embeddings are preloaded into memory ([sup1], available as [sup1] at Bioinformatics online) and a single process iterates through all protein pairs, placing the corresponding embeddings onto the GPU for inference, and then retrieving and…
Nisar Wani, Khalid Raza, Othman Soufan
High throughput multi-omics data generation coupled with heterogeneous genomic data fusion are defining new ways to build computational inference models. These models are scalable and can support very large genome sizes with the added advantage of exploiting additional biological knowledge from the integration…
Fabrizio F Borelli, Raphael Y de Camargo, David C Martins Jr, Luiz CS Rozante
'Luiz CS Rozante'] Background Gene regulatory networks (GRN) inference is an important bioinformatics problem in which the gene interactions need to be deduced from gene expression data, such as microarray data. Feature selection methods can be applied to this problem. A feature selection technique is composed by two…
Jian Wang, Chong Chen, Shiwei Li, Chaoyong Wang + 4 more
Convolutional Neural Networks (CNNs) have been widely applied in various edge computing devices based on intelligent sensors. However, due to the high computational demands of CNN tasks, the limited computing resources of edge intelligent terminal devices, and significant architectural differences among these devices…
Rok Češnovar, Erik Štrumbelj, Junwen Wang
We describe an efficient Bayesian parallel GPU implementation of two classic statistical models-the Lasso and multinomial logistic regression. We focus on parallelizing the key components: matrix multiplication, matrix inversion, and sampling from the full conditionals. Our GPU implementations of Bayesian Lasso and…
Alessandro Petrini, Marco Mesiti, Max Schubach, Marco Frasca + 7 more
The idea on which multi-core parSMURF builds is that all operations performed on the different parts of the partition can be assigned to multiple core/threads and processed in parallel. Namely, given q threads, the data parts N1, …, Nn are equally distributed among threads so that thread i receives a subset (chunk) Ci…
Raghuram Thiagarajan, Amir Alavi, Jagdeep T. Podichetty, Jason N. Bazil + 1 more
'Jason N. Bazil' 'Daniel A. Beard'] Systems research spanning fields from biology to finance involves the identification of models to represent the underpinnings of complex systems. Formal approaches for data-driven identification of network interactions include statistical inference-based approaches and methods to…
Ashish Chapagain, Dima Abuoliem, In Ho Cho, Tongbiao Wang
Multifunctional nanosurfaces receive growing attention due to their versatile properties. Capillary force lithography (CFL) has emerged as a simple and economical method for fabricating these surfaces. In recent works, the authors proposed to leverage the evolution strategies (ES) to modify nanosurface characteristics…
Benn Macdonald, Mu Niu, Simon Rogers, Maurizio Filippone + 1 more
'Dirk Husmeier'] Background A challenging problem in current systems biology is that of parameter inference in biological pathways expressed as coupled ordinary differential equations (ODEs). Conventional methods that repeatedly numerically solve the ODEs have large associated computational costs. Aimed at reducing…
Cristian Vidal-Silva, Vannessa Duarte, Jesennia Cárdenas-Cobo, Iván Veas
Parallel computing is a current algorithmic approach to looking for efficient solutions; that is, to define a set of processes in charge of performing at the same time the same task. Advances in hardware permit the massification of accessibility to and applications of parallel computing. Nonetheless, some algorithms…
Zeyu Xia, Canqun Yang, Chenchen Peng, Yifei Guo + 3 more
'Tao Tang' 'Yingbo Cui'] Background The advent of Single Molecule Real-Time (SMRT) sequencing has overcome many limitations of second-generation sequencing, such as limited read lengths, PCR amplification biases. However, longer reads increase data volume exponentially and high error rates make many existing alignment…
Gonzalo Vera, Ritsert C Jansen, Remo L Suppi
Background R is the preferred tool for statistical analysis of many bioinformaticians due in part to the increasing number of freely available analytical methods. Such methods can be quickly reused and adapted to each particular experiment. However, in experiments where large amounts of data are generated, for example…
Patrizio Dazzi
Embarrassingly parallel problems are characterised by a very small amount of information to be exchanged among the parts they are split in, during their parallel execution. As a consequence they do not require sophisticated, low-latency, high-bandwidth interconnection networks but can be efficiently computed in…