Biologically meaningful regulatory logic enhances the convergence rate in Boolean networks and bushiness of their state transition graph
Brief Bioinform. 2024 Mar 27;25(3):bbae150. doi: 10.1093/bib/bbae150.ABSTRACTBoolean models of gene regulatory networks (GRNs) have gained widespread traction as they can easily recapitulate cellular phenotypes via their attractor states. Their overall dynamics are embodied in a state transition graph (STG). Indeed, two Boolean networks (BNs) with the same network structure and attractors can have drastically different STGs depending on the type of Boolean functions (BFs) employed. Our objective here is to systematically delineate the effects of different classes of BFs on the structural features of the STG of reconstructe...
Source: Briefings in Bioinformatics - April 6, 2024 Category: Bioinformatics Authors: Priyotosh Sil Ajay Subbaroyan Saumitra Kulkarni Olivier C Martin Areejit Samal Source Type: research
A new paradigm for applying deep learning to protein-ligand interaction prediction
This study presents a novel framework for DL-based prediction of protein-ligand interactions, contributing to the advancement of this field. The IGModel is available at GitHub repository https://github.com/zchwang/IGModel.PMID:38581420 | PMC:PMC10998640 | DOI:10.1093/bib/bbae145 (Source: Briefings in Bioinformatics)
Source: Briefings in Bioinformatics - April 6, 2024 Category: Bioinformatics Authors: Zechen Wang Sheng Wang Yangyang Li Jingjing Guo Yanjie Wei Yuguang Mu Liangzhen Zheng Weifeng Li Source Type: research
PUTransGCN: identification of piRNA-disease associations based on attention encoding graph convolutional network and positive unlabelled learning
Brief Bioinform. 2024 Mar 27;25(3):bbae144. doi: 10.1093/bib/bbae144.ABSTRACTPiwi-interacting RNAs (piRNAs) play a crucial role in various biological processes and are implicated in disease. Consequently, there is an escalating demand for computational tools to predict piRNA-disease interactions. Although there have been computational methods proposed for the detection of piRNA-disease associations, the problem of imbalanced and sparse dataset has brought great challenges to capture the complex relationships between piRNAs and diseases. In response to this necessity, we have developed a novel computational architecture, de...
Source: Briefings in Bioinformatics - April 6, 2024 Category: Bioinformatics Authors: Qiuhao Chen Liyuan Zhang Yaojia Liu Zhonghao Qin Tianyi Zhao Source Type: research
From tradition to innovation: conventional and deep learning frameworks in genome annotation
Brief Bioinform. 2024 Mar 27;25(3):bbae138. doi: 10.1093/bib/bbae138.ABSTRACTFollowing the milestone success of the Human Genome Project, the 'Encyclopedia of DNA Elements (ENCODE)' initiative was launched in 2003 to unearth information about the numerous functional elements within the genome. This endeavor coincided with the emergence of numerous novel technologies, accompanied by the provision of vast amounts of whole-genome sequences, high-throughput data such as ChIP-Seq and RNA-Seq. Extracting biologically meaningful information from this massive dataset has become a critical aspect of many recent studies, particularl...
Source: Briefings in Bioinformatics - April 6, 2024 Category: Bioinformatics Authors: Zhaojia Chen Noor Ul Ain Qian Zhao Xingtan Zhang Source Type: research
Bayesian functional analysis for untargeted metabolomics data with matching uncertainty and small sample sizes
Brief Bioinform. 2024 Mar 27;25(3):bbae141. doi: 10.1093/bib/bbae141.ABSTRACTUntargeted metabolomics based on liquid chromatography-mass spectrometry technology is quickly gaining widespread application, given its ability to depict the global metabolic pattern in biological samples. However, the data are noisy and plagued by the lack of clear identity of data features measured from samples. Multiple potential matchings exist between data features and known metabolites, while the truth can only be one-to-one matches. Some existing methods attempt to reduce the matching uncertainty, but are far from being able to remove the ...
Source: Briefings in Bioinformatics - April 6, 2024 Category: Bioinformatics Authors: Guoxuan Ma Jian Kang Tianwei Yu Source Type: research
DeepFGRN: inference of gene regulatory network with regulation type based on directed graph embedding
Brief Bioinform. 2024 Mar 27;25(3):bbae143. doi: 10.1093/bib/bbae143.ABSTRACTThe inference of gene regulatory networks (GRNs) from gene expression profiles has been a key issue in systems biology, prompting many researchers to develop diverse computational methods. However, most of these methods do not reconstruct directed GRNs with regulatory types because of the lack of benchmark datasets or defects in the computational methods. Here, we collect benchmark datasets and propose a deep learning-based model, DeepFGRN, for reconstructing fine gene regulatory networks (FGRNs) with both regulation types and directions. In addit...
Source: Briefings in Bioinformatics - April 6, 2024 Category: Bioinformatics Authors: Zhen Gao Yansen Su Junfeng Xia Rui-Fen Cao Yun Ding Chun-Hou Zheng Pi-Jing Wei Source Type: research
GLDM: hit molecule generation with constrained graph latent diffusion model
Brief Bioinform. 2024 Mar 27;25(3):bbae142. doi: 10.1093/bib/bbae142.ABSTRACTDiscovering hit molecules with desired biological activity in a directed manner is a promising but profound task in computer-aided drug discovery. Inspired by recent generative AI approaches, particularly Diffusion Models (DM), we propose Graph Latent Diffusion Model (GLDM)-a latent DM that preserves both the effectiveness of autoencoders of compressing complex chemical data and the DM's capabilities of generating novel molecules. Specifically, we first develop an autoencoder to encode the molecular data into low-dimensional latent representations...
Source: Briefings in Bioinformatics - April 6, 2024 Category: Bioinformatics Authors: Conghao Wang Hiok Hian Ong Shunsuke Chiba Jagath C Rajapakse Source Type: research
Accuracy of AlphaFold models: Comparison with short N < sup > < sub > … < /sub > < /sup > O contacts in atomic resolution protein crystal structures
Comput Biol Chem. 2024 Apr 4;110:108069. doi: 10.1016/j.compbiolchem.2024.108069. Online ahead of print.ABSTRACTArtificial intelligence (AI) has revolutionized structural biology by predicting protein 3D structures with near-experimental accuracy. Here, short backbone N-O distances in high-resolution crystal structures were compared to those in three-dimensional models based on AI AlphaFold/ColabFold, specifically considering their estimated standard errors. Experimental and computationally modeled distances very often differ significantly, showing that these models' precision is inadequate to reproduce experimental result...
Source: Computational Biology and Chemistry - April 6, 2024 Category: Bioinformatics Authors: Oliviero Carugo Source Type: research
FaissMolLib: An efficient and easy deployable tool for ligand-based virtual screening
Comput Biol Chem. 2024 Apr 1;110:108057. doi: 10.1016/j.compbiolchem.2024.108057. Online ahead of print.ABSTRACTVirtual screening-based molecular similarity and fingerprint are crucial in drug design, target prediction, and ADMET prediction, aiding in identifying potential hits and optimizing lead compounds. However, challenges such as lack of comprehensive open-source molecular fingerprint databases and efficient search methods for virtual screening are prevalent. To address these issues, we introduce FaissMolLib, an open-source virtual screening tool that integrates 2.8 million compounds from ChEMBL and ZINC databases. N...
Source: Computational Biology and Chemistry - April 6, 2024 Category: Bioinformatics Authors: Haihan Liu Peiying Chen Baichun Hu Shizun Wang Hanxun Wang Jiasi Luan Jian Wang Bin Lin Maosheng Cheng Source Type: research
Optimal Rotation Age in Fast Growing Plantations: A Dynamical Optimization Problem
Bull Math Biol. 2024 Apr 6;86(5):51. doi: 10.1007/s11538-024-01262-8.ABSTRACTForest plantations are economically and environmentally relevant, as they play a key role in timber production and carbon capture. It is expected that the future climate change scenario affects forest growth and modify the rotation age for timber production. However, mathematical models on the effect of climate change on the rotation age for timber production remain still limited. We aim to determine the optimal rotation age that maximizes the net economic benefit of timber volume in a negative scenario from the climatic point of view. For this pu...
Source: Bulletin of Mathematical Biology - April 6, 2024 Category: Bioinformatics Authors: Alex Altamirano-Fern ández Alejandro Rojas-Palma Sergio Espinoza-Meza Source Type: research
Dynamics of Information Flow and Task Allocation of Social Insect Colonies: Impacts of Spatial Interactions and Task Switching
Bull Math Biol. 2024 Apr 6;86(5):50. doi: 10.1007/s11538-024-01280-6.ABSTRACTModels of social interaction dynamics have been powerful tools for understanding the efficiency of information spread and the robustness of task allocation in social insect colonies. How workers spatially distribute within the colony, or spatial heterogeneity degree (SHD), plays a vital role in contact dynamics, influencing information spread and task allocation. We used agent-based models to explore factors affecting spatial heterogeneity and information flow, including the number of task groups, variation in spatial arrangements, and levels of t...
Source: Bulletin of Mathematical Biology - April 6, 2024 Category: Bioinformatics Authors: Jun Chen Xiaohui Guo Daniel Charbonneau Asma Azizi Jennifer Fewell Yun Kang Source Type: research
Optimal Rotation Age in Fast Growing Plantations: A Dynamical Optimization Problem
Bull Math Biol. 2024 Apr 6;86(5):51. doi: 10.1007/s11538-024-01262-8.ABSTRACTForest plantations are economically and environmentally relevant, as they play a key role in timber production and carbon capture. It is expected that the future climate change scenario affects forest growth and modify the rotation age for timber production. However, mathematical models on the effect of climate change on the rotation age for timber production remain still limited. We aim to determine the optimal rotation age that maximizes the net economic benefit of timber volume in a negative scenario from the climatic point of view. For this pu...
Source: Bulletin of Mathematical Biology - April 6, 2024 Category: Bioinformatics Authors: Alex Altamirano-Fern ández Alejandro Rojas-Palma Sergio Espinoza-Meza Source Type: research
Dynamics of Information Flow and Task Allocation of Social Insect Colonies: Impacts of Spatial Interactions and Task Switching
Bull Math Biol. 2024 Apr 6;86(5):50. doi: 10.1007/s11538-024-01280-6.ABSTRACTModels of social interaction dynamics have been powerful tools for understanding the efficiency of information spread and the robustness of task allocation in social insect colonies. How workers spatially distribute within the colony, or spatial heterogeneity degree (SHD), plays a vital role in contact dynamics, influencing information spread and task allocation. We used agent-based models to explore factors affecting spatial heterogeneity and information flow, including the number of task groups, variation in spatial arrangements, and levels of t...
Source: Bulletin of Mathematical Biology - April 6, 2024 Category: Bioinformatics Authors: Jun Chen Xiaohui Guo Daniel Charbonneau Asma Azizi Jennifer Fewell Yun Kang Source Type: research
FaissMolLib: An efficient and easy deployable tool for ligand-based virtual screening
Comput Biol Chem. 2024 Apr 1;110:108057. doi: 10.1016/j.compbiolchem.2024.108057. Online ahead of print.ABSTRACTVirtual screening-based molecular similarity and fingerprint are crucial in drug design, target prediction, and ADMET prediction, aiding in identifying potential hits and optimizing lead compounds. However, challenges such as lack of comprehensive open-source molecular fingerprint databases and efficient search methods for virtual screening are prevalent. To address these issues, we introduce FaissMolLib, an open-source virtual screening tool that integrates 2.8 million compounds from ChEMBL and ZINC databases. N...
Source: Computational Biology and Chemistry - April 6, 2024 Category: Bioinformatics Authors: Haihan Liu Peiying Chen Baichun Hu Shizun Wang Hanxun Wang Jiasi Luan Jian Wang Bin Lin Maosheng Cheng Source Type: research
Accuracy of AlphaFold models: Comparison with short N < sup > < sub > … < /sub > < /sup > O contacts in atomic resolution protein crystal structures
Comput Biol Chem. 2024 Apr 4;110:108069. doi: 10.1016/j.compbiolchem.2024.108069. Online ahead of print.ABSTRACTArtificial intelligence (AI) has revolutionized structural biology by predicting protein 3D structures with near-experimental accuracy. Here, short backbone N-O distances in high-resolution crystal structures were compared to those in three-dimensional models based on AI AlphaFold/ColabFold, specifically considering their estimated standard errors. Experimental and computationally modeled distances very often differ significantly, showing that these models' precision is inadequate to reproduce experimental result...
Source: Computational Biology and Chemistry - April 6, 2024 Category: Bioinformatics Authors: Oliviero Carugo Source Type: research
