Results 51 to 60 of about 60,493 (305)

Diffusion‐Based Generative Model With Scaffold‐Hopping Strategy Yields Highly Potent Bioactive Molecules

Advanced Science, EarlyView.
SMarT‐Diff introduces a multi‐objective generative paradigm that integrates scaffold hopping with structure‐aware scoring to enable controlled exploration beyond the training distribution. The framework consistently balances drug‐likeness, synthesizes accessibility and bioactivity, yielding chemically diverse candidates with enhanced properties.
Yuwei Yang, Xiaoqing Gong, Shukai Gu, Jing Li, Bo Liu, Yanan Tian, Qianqian Zhang, Xiaojun Yao, Huanxiang Liu   +8 more
wiley   +1 more source

PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes

Advanced Science, EarlyView.
A plant genomic foundation model pre‐trained on 12 species enables both accurate gene prediction and de novo gene design. Through AI‐human knowledge screening, seven designed sequences showed transcriptional activity in plants, with two expressing stable proteins—demonstrating the first DNA‐RNA‐protein expression of LLM‐generated genes in plants and ...
Changhao Li, Qizhe Zhang, Hanchen Chen, Kepeng Lin, Chengfang Luo, Mengying Yang, Wei Xu, Fan Yao, Jianbing Yan, Qing‐Yong Yang, Xuehai Hu   +10 more
wiley   +1 more source

Riboswitch Detection Using Profile Hidden Markov Models

BMC Bioinformatics, 2009
Background Riboswitches are a type of noncoding RNA that regulate gene expression by switching from one structural conformation to another on ligand binding. The various classes of riboswitches discovered so far are differentiated by the ligand, which on
Krishnamachari A, Bhattacharya Sudha, Bandyopadhyay Pradipta, Singh Payal, Sengupta Supratim   +4 more
doaj   +1 more source

Dynamic Bayesian Networks for Audio-Visual Speech Recognition

EURASIP Journal on Advances in Signal Processing, 2002
The use of visual features in audio-visual speech recognition (AVSR) is justified by both the speech generation mechanism, which is essentially bimodal in audio and visual representation, and by the need for features that are invariant to acoustic noise
Liang Luhong, Pi Xiaobo, Liu Xiaoxing, Murphy Kevin, Nefian Ara V   +4 more
doaj   +1 more source

Hidden Markov Model Cryptanalysis [PDF]

, 2003
We present HMM attacks, a new type of cryptanalysis based on modeling randomized side channel countermeasures as Hidden Markov Models (HMM’s). We also introduce Input Driven Hidden Markov Models (IDHMM’s), a generalization of HMM’s that provides a powerful and unified cryptanalytic framework for analyzing countermeasures whose operational behavior can ...
Chris Karlof, David A. Wagner 0001
openaire   +1 more source

Partially-Hidden Markov Models [PDF]

, 2012
This paper addresses the problem of Hidden Markov Models (HMM) training and inference when the training data are composed of feature vectors plus uncertain and imprecise labels. The “soft” labels represent partial knowledge about the possible states at each time step and the “softness” is encoded by belief functions.
Emmanuel Ramasso, Thierry Denoeux, Noureddine Zerhouni   +2 more
openaire   +2 more sources

Full‐Stack Architectures for Intelligent Brain‐Computer Interfaces

Advanced Science, EarlyView.
System‐level overview of brain–computer interfaces (BCIs), illustrating the integration of neural signal acquisition, wireless transmission, and adaptive decoding. Advanced electrode, tissue interfaces, energy‐efficient communication, and robust algorithms collectively enable stable signal quality, real‐time processing, and closed‐loop operation ...
Hee Kyu Lee, Hyun Bin Kim, Sang Uk Park, Janghoon Joo, Jinhong Min, Geumbee Lee, Joohoon Kang, Hyoyoung Jeong, Jae‐Young Yoo, Sang Min Won   +9 more
wiley   +1 more source

Using features of local densities, statistics and HMM toolkit (HTK) for offline Arabic handwriting text recognition

Journal of Electrical Systems and Information Technology, 2017
This paper presents an analytical approach of an offline handwritten Arabic text recognition system. It is based on the Hidden Markov Models (HMM) Toolkit (HTK) without explicit segmentation. The first phase is preprocessing, where the data is introduced
El Moubtahij Hicham, Halli Akram, Satori Khalid   +2 more
doaj   +1 more source

Multiple-regression hidden Markov model [PDF]

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002
Proposes a class of hidden Markov model (HMM) called multiple-regression HMM (MR-HMM) that utilizes auxiliary features such as fundamental frequency (F/sub 0/) and speaking styles that affect spectral parameters to better model the acoustic features of phonemes.
Fujinaga, Katsuhisa, Nakai, Mitsuru, Shimodaira, Hiroshi, Sagayama, Shigeki   +3 more
openaire   +2 more sources

Hidden Markov Modeling Over Graphs

2022 IEEE Data Science and Learning Workshop (DSLW), 2022
This work proposes a multi-agent filtering algorithm over graphs for finite-state hidden Markov models (HMMs), which can be used for sequential state estimation or for tracking opinion formation over dynamic social networks. We show that the difference from the optimal centralized Bayesian solution is asymptotically bounded for geometrically ergodic ...
Mert Kayaalp, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed   +3 more
openaire   +2 more sources