25 papers · ranked by Valyu relevance
Haoyang Cao, Minshuo Chen, Yinbin Han, Renyuan Xu
Generating realistic synthetic sequential data is critical in real-world applications across operations research, finance, healthcare, energy systems, and scientific computing, where time-indexed observations are used for prediction, simulation, risk assessment, and data-driven decision-making. While diffusion models…
Paul Tiwald, Ivona Krchova, Andrey Sidorenko, Mariana Vargas-Vieyra + 2 more
Generating High-Fidelity Synthetic Data Authors: ['Paul Tiwald' 'Ivona Krchova' 'Andrey Sidorenko' 'Mariana Vargas-Vieyra' 'Mario Scriminaci' 'Michael Platzer'] Synthetic data generation for tabular datasets must balance fidelity, efficiency, and versatility to meet the demands of real-world applications. We introduce…
Zhimian Hao, Chonghuan Zhang, Alexei Lapkin
We propose a workflow for reduction in the time required for data generation during generation of statistical digital twins. This methodology is particularly relevant for real-world engineering problems when data generation is expensive. A prerequisite for building surrogates is sufficient input/output data, whereas…
Javier Geijo-Fernández, Alexander Pfundner, Carlos A Garcia-Perez
Microbial community profiling relies on comprehensive reference databases, yet full-length 16S rRNA amplicons remain sparse for many bacterial taxa. We present SGenerator, a neural network-based data augmentation method that generates biologically informative, full-length (1500 bp) 16S rRNA sequences for…
Keyi Li, Sen Yang, Travis M. Sullivan, Randall S. Burd + 1 more
Process data with confidential information cannot be shared directly in public, which hinders the research in process data mining and analytics. Data encryption methods have been studied to protect the data, but they still may be decrypted, which leads to individual identification. We experimented with different models…
Katariina Perkonoja, Kari Auranen, Joni Virta
The rapid growth in data availability has facilitated research and development, yet not all industries have benefited equally due to legal and privacy constraints. The healthcare sector faces significant challenges in utilizing patient data because of concerns about data security and confidentiality. To address this…
MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaïna Filali Boubrahimi
Learning Authors: ['MohammadReza EskandariNasab' 'Shah Muhammad Hamdi' 'Soukaïna Filali Boubrahimi'] Abstract—Current Generative Adversarial Network (GAN) based approaches for time series generation face challenges such as suboptimal convergence, information loss in embedding spaces, and instability. To overcome these…
Mst. Fahmida Sultana Naznin, Swarup Sidhartho Mondol, Adnan Ibney Faruq, Ahmed Mahir Sultan Rumi + 2 more
The fast-growing amount of data needs reliable and long-lasting storage solutions. DNA has emerged as a promising medium due to its high information density and long-term stability. However, DNA storage is a complex process where each stage introduces noise and errors, including synthesis errors, storage decay, and…
Nicola Mulberry, Tanja Stadler
A combination of recent advancements in molecular recording devices and sequencing technologies has made it possible to generate lineage tracing data on the order of thousands of cells. Dynamic lineage recorders are able to generate random, heritable mutations which accumulate continuously on the timescale of…
Debapriya Hazra, Mi-Ryung Kim, Yung-Cheol Byun, Luca Agnelli
Nucleic acids are the basic units of deoxyribonucleic acid (DNA) sequencing. Every organism demonstrates different DNA sequences with specific nucleotides. It reveals the genetic information carried by a particular DNA segment. Nucleic acid sequencing expresses the evolutionary changes among organisms and…
Sophie Seidel, Antoine Zwaans, Samuel Regalado, Junhong Choi + 2 more
CRISPR-based lineage tracing offers a promising avenue to decipher single cell lineage trees, especially in organisms that are challenging for microscopy. A recent advancement in this domain is lineage tracing based on sequential genome editing, which not only records genetic edits but also the order in which they…
Sohom Ghosh, Shefali Yadav, Xin Wang, Bibhash Chakrabarty + 1 more
'Serdar Kadıoğlu'] Sequential pattern mining remains a challenging task due to the large number of redundant candidate patterns and the exponential search space. In addition, further analysis is still required to map extracted patterns to different outcomes. In this paper, we introduce a pattern mining framework that…
D. Lin, Y. F. Ji, J. A. A. McArt, J. Li
While global medical research is poised to benefit from the rapid advance of artificial intelligence (AI) technologies, veterinary medicine research often faces significant limitations due to data scarcity and availability issues. To address this issue, we proposed a generative modeling framework, SynLS, for generating…
Aleksey Buzmakov, Elias Egho, Nicolas Jay, Sergei O. Kuznetsov + 2 more
'Amedeo Napoli' 'Chedy Raïssi'] Nowadays data sets are available in very complex and heterogeneous ways. Mining of such data collections is essential to support many realworld applications ranging from healthcare to marketing. In this work, we focus on the analysis of "complex" sequential data by means of interesting…
Osvaldo Navarro, René Cumplido, Luis Villaseñor-Pineda, Claudia Feregrino-Uribe + 2 more
'Claudia Feregrino-Uribe' 'Jesús Ariel Carrasco-Ochoa' 'Francesco Pappalardo'] Sequential Pattern Mining is a widely addressed problem in data mining, with applications such as analyzing Web usage, examining purchase behavior, and text mining, among others. Nevertheless, with the dramatic increase in data volume, the…
Authors not listed
Sequence is the critical determinant of macromolecular function, yet current polymer design approaches often optimize monomer composition and ratios while ignoring sequence. This creates poorly defined design spaces for active learning that miss the vast combinatorial landscape of sequence possibilities. We introduce…
Qi Zhang, Chang Liu, Stephen Wu, Ryo Yoshida
In the last few years, de novo molecular design using machine learning has made great technical progress but its practical deployment has not been as successful. This is mostly owing to the cost and technical difficulty of synthesizing such computationally designed molecules. To overcome such barriers, various methods…
Ovidiu Popa, Ellen Oldenburg, Oliver Ebenhöh
Today massive amounts of sequenced metagenomic and metatranscriptomic data from different ecological niches and environmental locations are available. Scientific progress depends critically on methods that allow extracting useful information from the various types of sequence data. Here, we will first discuss types of…
Rafał Deja, Wojciech Froelich, GraŻyna Deja
Background In spite of numerous research efforts on supporting the therapy of diabetes mellitus, the subject still involves challenges and creates active interest among researchers. In this paper, a decision support tool is presented for setting insulin therapy in new-onset type 1 diabetes. Methods The concept of…
Authors not listed
This research presents a novel approach to obstacle detection during navigation using a combination of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The primary objective is to generate accurate image captions that describe the content of images, which is crucial for applications such…
Kevin Kawchak
Large Multimodal Models (LMMs) possess the ability to analyze chemical spectra of an organic compound using state of the art conversational AI. These outputs can then be chained together and introduced as a text input for other LLMs or LMMs to predict the compound name. Here, a challenging 15 carbon molecule problem…
Sophie Seidel, Antoine Zwaans, Samuel Regalado, Junhong Choi + 2 more
CRISPR-based lineage tracing offers a promising avenue to decipher single cell lineage trees, especially in organisms that are challenging for microscopy. A recent advancement in this domain is lineage tracing based on sequential genome editing, which not only records genetic edits but also the order in which they…
Machiko Ohbayashi
The production of action sequences is a fundamental aspect of human motor skills. To examine whether primary motor cortex (M1) is involved in maintenance of sequential movements, we trained two monkeys (Cebus apella) to perform two sequential reaching tasks. In one task, sequential movements were instructed by visual…
Fritz Lekschas, Brant Peterson, Daniel Haehn, Eric Ma + 2 more
We present PEAX, a novel feature-based technique for interactive visual pattern search in sequential data, like time series or data mapped to a genome sequence. Visually searching for patterns by similarity is often challenging because of the large search space, the visual complexity of patterns, and the user’s…
Wenyu Zhang, Mason Guy, Jerrica Yang, Lucy Hao + 5 more
Large Language Models (LLMs) have revolutionized numerous industries as well as accelerated scientific research. However, their application in planning and conducting experimental science, has been limited. In this study, we introduce an adaptable prompt-set with GPT-4, converting literature experimental procedures…