DeepPLM_mCNN: An approach for enhancing ion channel and ion transporter recognition by multi-window CNN based on features from pre-trained language models
This study illustrates the potential of combining PLMs and deep learning for accurate computational identification of membrane proteins from sequence data alone. Our findings have important implications for membrane protein research and drug development targeting ion channels and transporters. The data and source codes in this study are publicly available at the following link: https://github.com/s1129108/DeepPLM_mCNN.PMID:38555810 | DOI:10.1016/j.compbiolchem.2024.108055 (Source: Computational Biology and Chemistry)
Source: Computational Biology and Chemistry - March 31, 2024 Category: Bioinformatics Authors: Van-The Le Muhammad-Shahid Malik Yi-Hsuan Tseng Yu-Cheng Lee Cheng-I Huang Yu-Yen Ou Source Type: research
Combinatorial Cooperativity in miR200-Zeb Feedback Network can Control Epithelial-Mesenchymal Transition
Bull Math Biol. 2024 Mar 30;86(5):48. doi: 10.1007/s11538-024-01277-1.ABSTRACTCarcinomas often utilize epithelial-mesenchymal transition (EMT) programs for cancer progression and metastasis. Numerous studies report SNAIL-induced miR200/Zeb feedback circuit as crucial in regulating EMT by placing cancer cells in at least three phenotypic states, viz. epithelial (E), hybrid (h-E/M), mesenchymal (M), along the E-M phenotypic spectrum. However, a coherent molecular-level understanding of how such a tiny circuit controls carcinoma cell entrance into and residence in various states is lacking. Here, we use molecular binding data...
Source: Bulletin of Mathematical Biology - March 30, 2024 Category: Bioinformatics Authors: Mubasher Rashid Brasanna M Devi Malay Banerjee Source Type: research
A cloud-based precision oncology framework for whole genome sequence analysis
Comput Biol Chem. 2024 Mar 28;110:108062. doi: 10.1016/j.compbiolchem.2024.108062. Online ahead of print.ABSTRACTCancer is one of the wide-ranging diseases which have a high mortality rate impacting globally. This scenario can be switched by early detection and correct precision treatment, a major concern for cancer patients. Clinicians can figure out the best-suited treatments for cancer patients by analyzing the patient's genome, which will treat the patient well and minimize the chances of side effects as well. Therefore, we have developed a fast, robust, and efficient solution as our precision oncology framework based ...
Source: Computational Biology and Chemistry - March 30, 2024 Category: Bioinformatics Authors: Saloni Tandon Medha Sharma Pratik Kasar Anirudh Kala Source Type: research
MS-BACL: enhancing metabolic stability prediction through bond graph augmentation and contrastive learning
Brief Bioinform. 2024 Mar 27;25(3):bbae127. doi: 10.1093/bib/bbae127.ABSTRACTMOTIVATION: Accurately predicting molecular metabolic stability is of great significance to drug research and development, ensuring drug safety and effectiveness. Existing deep learning methods, especially graph neural networks, can reveal the molecular structure of drugs and thus efficiently predict the metabolic stability of molecules. However, most of these methods focus on the message passing between adjacent atoms in the molecular graph, ignoring the relationship between bonds. This makes it difficult for these methods to estimate accurate mo...
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Tao Wang Zhen Li Linlin Zhuo Yifan Chen Xiangzheng Fu Quan Zou Source Type: research
DNA Bloom Filter enables anti-contamination and file version control for DNA-based data storage
Brief Bioinform. 2024 Mar 27;25(3):bbae125. doi: 10.1093/bib/bbae125.ABSTRACTDNA storage is one of the most promising ways for future information storage due to its high data storage density, durable storage time and low maintenance cost. However, errors are inevitable during synthesizing, storing and sequencing. Currently, many error correction algorithms have been developed to ensure accurate information retrieval, but they will decrease storage density or increase computing complexity. Here, we apply the Bloom Filter, a space-efficient probabilistic data structure, to DNA storage to achieve the anti-error, or anti-conta...
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Yiming Li Haoling Zhang Yuxin Chen Yue Shen Zhi Ping Source Type: research
Graph-pMHC: graph neural network approach to MHC class II peptide presentation and antibody immunogenicity
Brief Bioinform. 2024 Mar 27;25(3):bbae123. doi: 10.1093/bib/bbae123.ABSTRACTAntigen presentation on MHC class II (pMHCII presentation) plays an essential role in the adaptive immune response to extracellular pathogens and cancerous cells. But it can also reduce the efficacy of large-molecule drugs by triggering an anti-drug response. Significant progress has been made in pMHCII presentation modeling due to the collection of large-scale pMHC mass spectrometry datasets (ligandomes) and advances in machine learning. Here, we develop graph-pMHC, a graph neural network approach to predict pMHCII presentation. We derive adjacen...
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: William John Thrift Jason Perera Sivan Cohen Nicolas W Lounsbury Hem R Gurung Christopher M Rose Jieming Chen Suchit Jhunjhunwala Kai Liu Source Type: research
PANoptosis, an indicator of COVID-19 severity and outcomes
This study conducted a bioinformatics analysis of online single-cell RNA sequence (scRNA-seq) and bulk RNA-seq datasets to explore the potential of PANoptosis as an indicator of COVID-19 severity. The degree of PANoptosis in bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells (PBMC) indicated the severity of COVID-19. Single-cell transcriptomics identified pro-inflammatory monocytes as one of the primary sites of PANoptosis in COVID-19. The study subsequently demonstrated the immune and metabolic characteristics of this group of pro-inflammatory monocytes. In addition, the analysis illustrated that d...
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Qingyuan Yang Wanmei Song Hanizaier Reheman Dan Wang Jieming Qu Yanan Li Source Type: research
D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer
Brief Bioinform. 2024 Mar 27;25(3):bbae121. doi: 10.1093/bib/bbae121.ABSTRACTAs key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal growth factor receptor (EGFR) with variable drug sensitivities have been a major obstacle for precision medicine. To achieve clinical-level drug recommendations, a platform for clinical patient case retrieval and reliable drug sensitivity prediction is highly expected. Therefore, we built a database, D3EGFRdb, with the clinicopathologic characteristics and drug responses of 1339 patients with EGFR mutations via literature mining. On the basis of D3EG...
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Yulong Shi Chongwu Li Xinben Zhang Cheng Peng Peng Sun Qian Zhang Leilei Wu Ying Ding Dong Xie Zhijian Xu Weiliang Zhu Source Type: research
FAIR Header Reference genome: a TRUSTworthy standard
The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.PMID:38555475 | PMC:PMC10981671 | DOI:10.1093/bib/bbae122 (Source: Briefings in Bioinformatics)
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Adam Wright Mark D Wilkinson Christopher Mungall Scott Cain Stephen Richards Paul Sternberg Ellen Provin Jonathan L Jacobs Scott Geib Daniela Raciti Karen Yook Lincoln Stein David C Molik Source Type: research
Benchmarking digital PCR partition classification methods with empirical and simulated duplex data
Brief Bioinform. 2024 Mar 27;25(3):bbae120. doi: 10.1093/bib/bbae120.ABSTRACTDigital PCR (dPCR) is a highly accurate technique for the quantification of target nucleic acid(s). It has shown great potential in clinical applications, like tumor liquid biopsy and validation of biomarkers. Accurate classification of partitions based on end-point fluorescence intensities is crucial to avoid biased estimators of the concentration of the target molecules. We have evaluated many clustering methods, from general-purpose methods to specific methods for dPCR and flowcytometry, on both simulated and real-life data. Clustering method p...
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Yao Chen Ward De Spiegelaere Wim Trypsteen David Gleerup Jo Vandesompele Antoon Lievens Matthijs Vynck Olivier Thas Source Type: research
A microbial knowledge graph-based deep learning model for predicting candidate microbes for target hosts
Brief Bioinform. 2024 Mar 27;25(3):bbae119. doi: 10.1093/bib/bbae119.ABSTRACTPredicting interactions between microbes and hosts plays critical roles in microbiome population genetics and microbial ecology and evolution. How to systematically characterize the sophisticated mechanisms and signal interplay between microbes and hosts is a significant challenge for global health risks. Identifying microbe-host interactions (MHIs) can not only provide helpful insights into their fundamental regulatory mechanisms, but also facilitate the development of targeted therapies for microbial infections. In recent years, computational me...
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Jie Pan Zhen Zhang Ying Li Jiaoyang Yu Zhuhong You Chenyu Li Shixu Wang Minghui Zhu Fengzhi Ren Xuexia Zhang Yanmei Sun Shiwei Wang Source Type: research
Advances in phage-host interaction prediction: in silico method enhances the development of phage therapies
Brief Bioinform. 2024 Mar 27;25(3):bbae117. doi: 10.1093/bib/bbae117.ABSTRACTPhages can specifically recognize and kill bacteria, which lead to important application value of bacteriophage in bacterial identification and typing, livestock aquaculture and treatment of human bacterial infection. Considering the variety of human-infected bacteria and the continuous discovery of numerous pathogenic bacteria, screening suitable therapeutic phages that are capable of infecting pathogens from massive phage databases has been a principal step in phage therapy design. Experimental methods to identify phage-host interaction (PHI) ar...
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Wanchun Nie Tianyi Qiu Yiwen Wei Hao Ding Zhixiang Guo Jingxuan Qiu Source Type: research
scNovel: a scalable deep learning-based network for novel rare cell discovery in single-cell transcriptomics
Brief Bioinform. 2024 Mar 27;25(3):bbae112. doi: 10.1093/bib/bbae112.ABSTRACTSingle-cell RNA sequencing has achieved massive success in biological research fields. Discovering novel cell types from single-cell transcriptomics has been demonstrated to be essential in the field of biomedicine, yet is time-consuming and needs prior knowledge. With the unprecedented boom in cell atlases, auto-annotation tools have become more prevalent due to their speed, accuracy and user-friendly features. However, existing tools have mostly focused on general cell-type annotation and have not adequately addressed the challenge of discoverin...
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Chuanyang Zheng Yixuan Wang Yuqi Cheng Xuesong Wang Hongxin Wei Irwin King Yu Li Source Type: research
FAIR Header Reference genome: a TRUSTworthy standard
The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.PMID:38555475 | DOI:10.1093/bib/bbae122 (Source: Briefings in Bioinformatics)
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Adam Wright Mark D Wilkinson Christopher Mungall Scott Cain Stephen Richards Paul Sternberg Ellen Provin Jonathan L Jacobs Scott Geib Daniela Raciti Karen Yook Lincoln Stein David C Molik Source Type: research
Graph-pMHC: graph neural network approach to MHC class II peptide presentation and antibody immunogenicity
Brief Bioinform. 2024 Mar 27;25(3):bbae123. doi: 10.1093/bib/bbae123.ABSTRACTAntigen presentation on MHC class II (pMHCII presentation) plays an essential role in the adaptive immune response to extracellular pathogens and cancerous cells. But it can also reduce the efficacy of large-molecule drugs by triggering an anti-drug response. Significant progress has been made in pMHCII presentation modeling due to the collection of large-scale pMHC mass spectrometry datasets (ligandomes) and advances in machine learning. Here, we develop graph-pMHC, a graph neural network approach to predict pMHCII presentation. We derive adjacen...
Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: William John Thrift Jason Perera Sivan Cohen Nicolas W Lounsbury Hem R Gurung Christopher M Rose Jieming Chen Suchit Jhunjhunwala Kai Liu Source Type: research
