25 papers · ranked by Valyu relevance
Matthew S. Schmitt, Kiseok K. Lee, Freddy Bunbury, Joseph A. Landsittel + 2 more
From soil to the gut, communities composed of thousands of microbes perform functions such as carbon sequestration and immune system regulation. Here, we introduce a data-driven approach that explains how community function can be traced to just a few groups of microbes or genes. In gut communities, our neural-network…
Felix Moorhoff, David Medina-Ortiz, Alicja Kotnis, Ahmed Hassanin + 1 more
The rapid expansion of protein sequence databases continues to outpace functional characterization, creating a persistent bottleneck in enzyme discovery and mining—particularly in large, heterogeneous, and sparsely annotated sequence spaces. This gap is amplified by visualization challenges and the lack of informed…
Xiang Ma, Parnal Joshi, Iddo Friedberg, Qi Li
Predicting enzyme function from its sequence is still an unsolved problem in the life sciences. Moreover, with the explosion of annotated genome data, we are inundated with potential enzymatic sequences that have not yet been biochemically characterized. While it is not possible to assign a not-yet-existing label to…
Hanwen Luo, Sichao Qiu, Maozu Guo, Beibei Xin + 2 more
Proteoforms translated from alternatively spliced transcripts contribute to the functional repertoire of the cell by performing diverse biological functions, contributing to the functional diversity of genomics and proteomics. However, the lack of existing databases that integrate functional annotations of proteoforms…
Kyoung-Kuk Kim, Donghwa Seo
We analyze intentional block delays (mining gaps) in Proof-of-Work blockchain systems, where miners strategically balance mining rewards against operational costs. Using a game-theoretic model, we derive a Nash equilibrium with optimal mining strategies and establish necessary and sufficient conditions for mining gap…
Yu Zhang, Minan Wang, Yangyang Sun, Hao Gao + 2 more
Amplicon sequencing enables taxonomic profiling of microbial communities but offers limited insight into their functional potential. Existing tools such as Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) infer functions through phylogenetic placement and ancestral state…
Yanping Xu, Hao Ren, Ziping Zou, Guohua Shen + 4 more
The mechanisms by which iron ore mining activities affect the surrounding rhizobacterial ecology remain unclear. This study employed 16S rRNA high-throughput sequencing to analyze the structure and function of rhizosphere bacterial communities associated with three local crops, Musa basjoo Siebold L., Triticum aestivum…
Tsz Ki Chan, Xingxing Wei, Li Ma, Hang Wang + 2 more
Gene-Guided Discovery of a Fungal Spirotetramate as an Acetolactate Synthase Inhibitor Authors: Tsz Ki Chan, Xingxing Wei, Li Ma, Hang Wang, Pan Liao, Yudai Matsuda Biosynthetic gene clusters (BGCs) of bioactive natural products occasionally encode resistant versions of the proteins they inhibit, offering opportunities…
Nathaniel S. S. Smith, Xinyu Yuan, Chesney Melissinos, Sahaj Satani + 2 more
The functional annotation of plant genes lags significantly behind their genomic annotation. Closing this gap requires thorough cataloging of reported protein activities alongside predictive methods that scale beyond sequence-similarity inference. Focusing on the BAHD acyltransferase enzyme family as a model, we…
Amay A. Agrawal, Chantal D. Bader, Ronald Garcia, Rolf Müller + 1 more
Microbial natural products represent a chemically diverse repertoire of small molecules with major pharmaceutical potential. Despite the increasing availability of microbial genome sequences, large-scale natural product discovery remains challenging because the existing genome mining approaches lack integrated…
Chen, Chunsong, Hou, Yichen + 7 more
In this study, we proposed a Multi-level Building Function Optimization (ML-BFO) method. It consists of three core stages: (1) Candidate function label generation; (2) Iterative label distribution refinement; and (3) Function-related label correction, as shown in Fig. 4. Moreover, we further design the Building…
Authors not listed
Realizing the promise of artificial intelligence (AI) to accelerate scientific progress and deliver technological impact depends on how effectively AI can be integrated into real-world decision- making processes. As Peter Norvig states, “Somewhat remarkably, almost all AI research until very recently has assumed that…
Jacob H. Wynne, Nima Azbijari, Andrew R. Thurber, Maude M. David
Remote functional annotation continues to impede progress in microbial ecology, as alignment-based approaches still leave over one-third of microbial sequences functionally unresolved. In contrast, pre-trained natural-language–processing approaches have shown strong potential for inferring functions from diverse…
Karla P. López-Martínez, Stephanie Hereira-Pacheco, Diana Hernández-Oaxaca, Frida López-Ruiz + 1 more
Metagenomics enables the recovery of metagenome-assembled genomes (MAGs), providing access to the metabolic potential of uncultured microbial communities that drive ecosystem function and biogeochemical cycles. However, as MAGs datasets increase in size and complexity, comparing functional repertoires and identifying…
Weiwei Zhou, Youfeng Zou, Huabin Chai, Miaomiao Ma + 3 more
With the expansion of underground coal mining, accurate prediction of surface subsidence dynamics has become increasingly critical. This study proposes a hybrid prediction framework integrating Differential Interferometric Synthetic Aperture Radar (D-InSAR) and the Boltzmann time function to address this challenge. In…
Suhyeon Lee, Hyeongyeong Kim
—We analyze Qubic's advertised selfish mining campaign on Monero in 2025. Combining data from Monero nodes, and the Qubic pool API, we reconstruct Qubicattributed blocks and hashrate and detect ten intervals consistent with selfish mining strategies. In these intervals, Qubic's average hashrate share rises to the…
Rund Tawfiq, Maxat Kulmanov, Robert Hoehndorf
Protein function annotation traditionally follows a reductionist approach, assigning functions to individual proteins acting in isolation. This treats each annotation as an independent fact, disconnected from the broader biological system. However, proteins operate within integrated networks where their functions…
Pierre-Olivier Goffard, Hansjoerg Albrecher, Jean-Pierre Fouque
Mining blocks in a blockchain using the Proof-of-Work consensus protocol involves significant risk, as network participants face continuous operational costs while earning infrequent capital gains upon successfully mining a block. A common risk mitigation strategy is to join a mining pool, which combines the computing…
Idan Daniel Grosbard, Mor Geva, Galit Yovel
A central goal in understanding human vision is to uncover the visual features that drive neuronal activity. A growing body of work has used artificial neural networks as encoding models to predict cortical responses to natural images, revealing the visual content that activates category-selective regions. However…
Alexander Adrian-Hamazaki, Paul Pavlidis
It is widely accepted in genomics that coexpression of RNA transcripts suggests a commonality of function. This intuition is explicitly leveraged in machine learning methods that predict gene function, where it is often combined with other features such as protein interactions and sequence similarity. For example…
Authors not listed
Iron, the most abundant element on Earth by mass (34.6%), primarily exists as iron minerals due to its inherent reactivity. The study of iron mineral phase transformations under changing environmental conditions remains an important research focus due to its geological, environmental, and industrial significance. Yet…
Zach Manson, Barry C. Sanders
We study the impact that two miners equipped with quantum computers purpose-built for quantum Bitcoin mining will have on the 51% attack threshold of the Bitcoin network, given that the miners are playing a competitive game against each other to be the first to mine a block. We extend an existing game-theoretic…
Avinash Kadimisetty, C. Oswald, B. Sivalselvan
The paper focuses on Image Compression, explaining efficient approaches based on Frequent Pattern Mining(FPM). The proposed compression mechanism is based on clustering similar pixels in the image and thus using cluster identifiers in image compression. Redundant data in the image is effectively handled by replacing…
Authors not listed
Elevated concentrations of critical metals (CM) in acid mine drainage (AMD) have been the subject of many studies due to high demand that is only expected to grow. Some, like rare earth elements (REEs) and Co are an essential component to many modern technologies. Previously we developed a CM recovery technique wherein…
Authors not listed
The reprocessing of concentrator tailings is a significant challenge in advancing a circular economy within the mining sector. Conventional flotation collectors frequently demonstrate low selectivity and efficiency when processing complex, low-grade ores. This study evaluates the efficacy of a novel heterocyclic…