journal
https://read.qxmd.com/read/38532297/pycom-a-python-library-for-large-scale-analysis-of-residue-residue-coevolution-data
#1
JOURNAL ARTICLE
Philipp Bibik, Sabriyeh Alibai, Alessandro Pandini, Sarath Chandra Dantu
MOTIVATION: Computational methods to detect correlated amino acid positions in proteins have become a valuable tool to predict intra and inter-residue protein contacts, protein structures, and effects of mutation on protein stability and function. While there are many tools and webservers to compute coevolution scoring matrices, there is no central repository of alignments and coevolution matrices for large-scale studies and pattern detection leveraging on structural and biological annotation already available in UniProt...
March 26, 2024: Bioinformatics
https://read.qxmd.com/read/38532295/pycomo-a-python-package-for-community-metabolic-model-creation-and-analysis
#2
JOURNAL ARTICLE
Michael Predl, Marianne Mießkes, Thomas Rattei, Jürgen Zanghellini
SUMMARY: PyCoMo is a python package for quick and easy generation of genome-scale compartmentalised community metabolic models that are compliant with current openCOBRA file formats. The resulting models can be used to predict (i) the maximum growth rate at a given abundance profile, (ii) the feasible community compositions at a given growth rate, and (iii) all exchange metabolites and cross-feeding interactions in a community metabolic model independent of the abundance profile; we demonstrate PyCoMo's capability by analysing methane production in a previously published simplified biogas community metabolic model (Koch et al...
March 26, 2024: Bioinformatics
https://read.qxmd.com/read/38530977/hypertmo-a-trusted-multi-omics-integration-framework-based-on-hypergraph-convolutional-network-for-patient-classification
#3
JOURNAL ARTICLE
Haohua Wang, Kai Lin, Qiang Zhang, Jinlong Shi, Xinyu Song, Jue Wu, Chenghui Zhao, Kunlun He
MOTIVATION: The rapid development of high-throughput biomedical technologies can provide researchers with detailed multi-omics data. The multi-omics integrated analysis approach based on machine learning contributes a more comprehensive perspective to human disease research. However, there are still significant challenges in representing single-omics data and integrating multi-omics information. RESULTS: This paper presents HyperTMO, a Trusted Multi-Omics integration framework based on Hypergraph convolutional network for patient classification...
March 26, 2024: Bioinformatics
https://read.qxmd.com/read/38530800/niend-neuronal-image-enhancement-through-noise-disentanglement
#4
JOURNAL ARTICLE
Zuo-Han Zhao, Yufeng Liu
MOTIVATION: The full automation of digital neuronal reconstruction from light microscopic images has long been impeded by noisy neuronal images. Previous endeavors to improve image quality can hardly get a good compromise between robustness and computational efficiency. RESULTS: We present the image enhancement pipeline named Neuronal Image Enhancement through Noise Disentanglement (NIEND). Through extensive benchmarking on 863 mouse neuronal images with manually annotated gold standards, NIEND achieves remarkable improvements in image quality such as signal-background contrast (40-fold) and background uniformity (10-fold), compared to raw images...
March 26, 2024: Bioinformatics
https://read.qxmd.com/read/38530779/molemcl-a-multi-level-contrastive-learning-framework-for-molecular-pre-training
#5
JOURNAL ARTICLE
Xinyi Zhang, Yanni Xu, Changzhi Jiang, Lian Shen, Xiangrong Liu
MOTIVATION: Molecular representation learning plays an indispensable role in crucial tasks such as property prediction and drug design. Despite the notable achievements of Molecular Pre-training Models (MPMs), current methods often fail to capture both the structural and feature semantics of molecular graphs. Moreover, while graph contrastive learning has unveiled new prospects, existing augmentation techniques often struggle to retain their core semantics. To overcome these limitations, we propose a gradient-compensated encoder parameter perturbation approach, ensuring efficient and stable feature augmentation...
March 26, 2024: Bioinformatics
https://read.qxmd.com/read/38530778/graphpath-a-graph-attention-model-for-molecular-stratification-with-interpretability-based-on-the-pathway-pathway-interaction-network
#6
JOURNAL ARTICLE
Teng Ma, Jianxin Wang
MOTIVATION: Studying the molecular heterogeneity of cancer is essential for achieving personalized therapy. At the same time, understanding the biological processes that drive cancer development can lead to the identification of valuable therapeutic targets. Therefore, achieving accurate and interpretable clinical predictions requires paramount attention to thoroughly characterizing patients at both the molecular and biological pathway levels. RESULTS: Here, we present GraphPath, a biological knowledge-driven graph neural network with multi-head self-attention mechanism that implements the pathway-pathway interaction network...
March 26, 2024: Bioinformatics
https://read.qxmd.com/read/38514422/integrating-physics-in-deep-learning-algorithms-a-force-field-as-a-pytorch-module
#7
JOURNAL ARTICLE
Gabriele Orlando, Luis Serrano, Joost Schymkowitz, Frederic Rousseau
MOTIVATION: Deep learning algorithms applied to structural biology often struggle to converge to meaningful solutions when limited data is available, since they are required to learn complex physical rules from examples. State-of-the-art force-fields, however, cannot interface with deep learning algorithms due to their implementation. RESULTS: We present MadraX, a forcefield implemented as a differentiable PyTorch module, able to interact with deep learning algorithms in an end-to-end fashion...
March 21, 2024: Bioinformatics
https://read.qxmd.com/read/38514421/alerax-a-tool-for-gene-and-species-tree-co-estimation-and-reconciliation-under-a-probabilistic-model-of-gene-duplication-transfer-and-loss
#8
JOURNAL ARTICLE
Benoit Morel, Tom A Williams, Alexandros Stamatakis, Gergely J Szöllősi
MOTIVATION: Genomes are a rich source of information on the pattern and process of evolution across biological scales. How best to make use of that information is an active area of research in phylogenetics. Ideally, phylogenetic methods should not only model substitutions along gene trees, which explain differences between homologous gene sequences, but also the processes that generate the gene trees themselves along a shared species tree. To conduct accurate inferences, one needs to account for uncertainty at both levels, that is, in gene trees estimated from inherently short sequences and in their diverse evolutionary histories along a shared species tree...
March 21, 2024: Bioinformatics
https://read.qxmd.com/read/38514403/a-model-based-hierarchical-bayesian-approach-to-sholl-analysis
#9
JOURNAL ARTICLE
Erik VonKaenel, Alexis Feidler, Rebecca Lowery, Katherine Andersh, Tanzy Love, Ania Majewska, Matthew N McCall
MOTIVATION: Due to the link between microglial morphology and function, morphological changes in microglia are frequently used to identify pathological immune responses in the central nervous system. In the absence of pathology, microglia are responsible for maintaining homeostasis, and their morphology can be indicative of how the healthy brain behaves in the presence of external stimuli and genetic differences. Despite recent interest in high throughput methods for morphological analysis, Sholl analysis is still widely used for quantifying microglia morphology via imaging data...
March 21, 2024: Bioinformatics
https://read.qxmd.com/read/38514400/advancing-entity-recognition-in-biomedicine-via-instruction-tuning-of-large-language-models
#10
JOURNAL ARTICLE
Vipina K Keloth, Yan Hu, Qianqian Xie, Xueqing Peng, Yan Wang, Andrew Zheng, Melih Selek, Kalpana Raja, Chih Hsuan Wei, Qiao Jin, Zhiyong Lu, Qingyu Chen, Hua Xu
MOTIVATION: Large Language Models (LLMs) have the potential to revolutionize the field of Natural Language Processing (NLP), excelling not only in text generation and reasoning tasks but also in their ability for zero/few-shot learning, swiftly adapting to new tasks with minimal fine-tuning. LLMs have also demonstrated great promise in biomedical and healthcare applications. However, when it comes to Named Entity Recognition (NER), particularly within the biomedical domain, LLMs fall short of the effectiveness exhibited by fine-tuned domain-specific models...
March 21, 2024: Bioinformatics
https://read.qxmd.com/read/38507691/contrastive-pre-training-and-3d-convolution-neural-network-for-rna-and-small-molecule-binding-affinity-prediction
#11
JOURNAL ARTICLE
Saisai Sun, Lin Gao
MOTIVATION: The diverse structures and functions inherent in RNAs present a wealth of potential drug targets. Some small molecules are anticipated to serve as leading compounds, providing guidance for the development of novel RNA-targeted therapeutics. Consequently, the determination of RNA-small molecule binding affinity is a critical undertaking in the landscape of RNA-targeted drug discovery and development. Nevertheless, to date, no computational method for RNA-small molecule binding affinity prediction has been proposed...
March 20, 2024: Bioinformatics
https://read.qxmd.com/read/38507682/temstapro-protein-thermostability-prediction-using-sequence-representations-from-protein-language-models
#12
JOURNAL ARTICLE
Ieva Pudžiuvelytė, Kliment Olechnovič, Egle Godliauskaite, Kristupas Sermokas, Tomas Urbaitis, Giedrius Gasiunas, Darius Kazlauskas
MOTIVATION: Reliable prediction of protein thermostability from its sequence is valuable for both academic and industrial research. This prediction problem can be tackled using machine learning and by taking advantage of the recent blossoming of deep learning methods for sequence analysis. These methods can facilitate training on more data and, possibly, enable development of more versatile thermostability predictors for multiple ranges of temperatures. RESULTS: We applied the principle of transfer learning to predict protein thermostability using embeddings generated by protein language models (pLMs) from an input protein sequence...
March 20, 2024: Bioinformatics
https://read.qxmd.com/read/38502961/ginsa-an-accumulator-for-paired-locality-and-next-generation-small-ribosomal-subunit-sequence-data
#13
JOURNAL ARTICLE
Eric Odle, Samual Kahng, Siratee Riewluang, Kyoko Kurihara, Kevin C Wakeman
MOTIVATION: Motivated by the challenges of decentralized genetic data spread across multiple international organizations, GINSA leverages the Global Biodiversity Information Facility (GBIF) infrastructure to automatically retrieve and link small ribosomal subunit (SSU) sequences with locality information. RESULTS: Testing on taxa from major organism groups demonstrates broad applicability across taxonomic levels and dataset sizes. AVAILABILITY: GINSA is a freely accessible Python program under the MIT License and can be installed from PyPI via pip...
March 19, 2024: Bioinformatics
https://read.qxmd.com/read/38498849/claudio-automated-structural-analysis-of-cross-linking-data
#14
JOURNAL ARTICLE
Alexander Röhl, Eugen Netz, Oliver Kohlbacher, Hadeer Elhabashy
MOTIVATION: Cross-linking mass spectrometry has made remarkable advancements in the high-throughput characterization of protein structures and interactions. The resulting pairs of cross-linked peptides typically require geometric assessment and validation, given the availability of their corresponding structures. RESULTS: CLAUDIO is an open-source software tool designed for the automated analysis and validation of different varieties of large-scale cross-linking experiments...
March 18, 2024: Bioinformatics
https://read.qxmd.com/read/38498847/fast-peak-error-correction-algorithms-for-proteoform-identification-using-top-down-tandem-mass-spectra
#15
JOURNAL ARTICLE
Zhaohui Zhan, Lusheng Wang
MOTIVATION: Proteoform identification is an important problem in proteomics. The main task is to find a modified protein that best fits the input spectrum. To overcome the combinatorial explosion of possible proteoforms, the proteoform mass graph and spectrum mass graph are used to represent the protein database and the spectrum, respectively. The problem becomes finding an optimal alignment between the proteoform mass graph and the spectrum mass graph. Peak error correction is an important issue for computing an optimal alignment between the two input mass graphs...
March 18, 2024: Bioinformatics
https://read.qxmd.com/read/38492564/consult-ii-accurate-taxonomic-identification-and-profiling-using-locality-sensitive-hashing
#16
JOURNAL ARTICLE
Ali Osman Berk Şapcı, Eleonora Rachtman, Siavash Mirarab
MOTIVATION: Taxonomic classification of short reads and taxonomic profiling of metagenomic samples are well-studied yet challenging problems. The presence of species belonging to ranks without close representation in a reference dataset is particularly challenging. While k-mer-based methods have performed well in terms of running time and accuracy, they tend to have reduced accuracy for such novel species. Thus, there is a growing need for methods that combine the scalability of k-merswith increased sensitivity...
March 16, 2024: Bioinformatics
https://read.qxmd.com/read/38490256/admix-kit-an-integrated-toolkit-and-pipeline-for-genetic-analyses-of-admixed-populations
#17
JOURNAL ARTICLE
Kangcheng Hou, Stephanie Gogarten, Joohyun Kim, Xing Hua, Julie-Alexia Dias, Quan Sun, Ying Wang, Taotao Tan, Elizabeth G Atkinson, Alicia Martin, Jonathan Shortt, Jibril Hirbo, Yun Li, Bogdan Pasaniuc, Haoyu Zhang
SUMMARY: Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic study of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations...
March 15, 2024: Bioinformatics
https://read.qxmd.com/read/38490248/icellnet-v2-a-versatile-method-for-cell-cell-communication-analysis-from-human-transcriptomic-data
#18
JOURNAL ARTICLE
Lucile Massenet-Regad, Vassili Soumelis
SUMMARY: Several methods have been developed in the past years to infer cell-cell communication networks from transcriptomic data based on ligand and receptor expression. Among them, ICELLNET is one of the few approaches to consider the multiple subunits of ligands and receptors complexes to infer and quantify cell communication. In here, we present a major update of ICELLNET. As compared to its original implementation, we 1) drastically expanded the ICELLNET ligand-receptor database from 380 to 1669 biologically curated interactions, 2) integrated important families of communication molecules involved in immune crosstalk, cell adhesion, and Wnt pathway, 3) optimized ICELLNET framework for single-cell RNA sequencing data analyses, 4) provided new visualizations of cell-cell communication results to facilitate prioritization and biological interpretation...
March 15, 2024: Bioinformatics
https://read.qxmd.com/read/38485700/vizapa-visualizing-dynamics-of-alternative-polyadenylation-from-bulk-and-single-cell-data
#19
JOURNAL ARTICLE
Xingyu Bi, Wenbin Ye, Xin Cheng, Ning Yang, Xiaohui Wu
MOTIVATION: Alternative polyadenylation (APA) is a widespread post-transcriptional regulatory mechanism across all eukaryotes. With the accumulation of genome-wide APA sites, especially those with single-cell resolution, it is imperative to develop easy-to-use visualization tools to guide APA analysis. RESULTS: We developed an R package called vizAPA for visualizing APA dynamics from bulk and single-cell data. vizAPA implements unified data structures for APA data and genome annotations...
March 14, 2024: Bioinformatics
https://read.qxmd.com/read/38485699/lambda3-homology-search-for-protein-nucleotide-and-bisulfite-converted-sequences
#20
JOURNAL ARTICLE
Hannes Hauswedell, Sara Hetzel, Simon G Gottlieb, Helene Kretzmer, Alexander Meissner, Knut Reinert
MOTIVATION: Local alignments of query sequences in large databases represent a core part of metagenomic studies and facilitate homology search. Following the development of NCBI Blast, many applications aimed to provide faster and equally sensitive local alignment frameworks. Most applications focus on protein alignments, while only few also facilitate DNA-based searches. None of the established programs allow searching DNA sequences from bisulfite sequencing experiments commonly used for DNA methylation profiling, for which specific alignment strategies need to be implemented...
March 14, 2024: Bioinformatics
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