Using protein language models for protein interaction hot spot prediction with limited data
Protein language models, inspired by the success of large language models in deciphering human language, have emerged as powerful tools for unraveling the intricate code of life inscribed within protein sequen... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 16, 2024 Category: Bioinformatics Authors: Karen Sargsyan and Carmay Lim Tags: Research Source Type: research
Integration of scRNA-seq data by disentangled representation learning with condition domain adaptation
The integration of single-cell RNA sequencing data from multiple experimental batches and diverse biological conditions holds significant importance in the study of cellular heterogeneity. (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 16, 2024 Category: Bioinformatics Authors: Renjing Liu, Kun Qian, Xinwei He and Hongwei Li Tags: Research Source Type: research
eSVD-DE: cohort-wide differential expression in single-cell RNA-seq data using exponential-family embeddings
Single-cell RNA-sequencing (scRNA) datasets are becoming increasingly popular in clinical and cohort studies, but there is a lack of methods to investigate differentially expressed (DE) genes among such datase... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 15, 2024 Category: Bioinformatics Authors: Kevin Z. Lin, Yixuan Qiu and Kathryn Roeder Tags: Research Source Type: research
NeuronBridge: an intuitive web application for neuronal morphology search across large data sets
Neuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. To exploit this knowledge base, r... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 15, 2024 Category: Bioinformatics Authors: Jody Clements, Cristian Goina, Philip M. Hubbard, Takashi Kawase, Donald J. Olbris, Hideo Otsuna, Robert Svirskas and Konrad Rokicki Tags: Software Source Type: research
MetaTron: advancing biomedical annotation empowering relation annotation and collaboration
The constant growth of biomedical data is accompanied by the need for new methodologies to effectively and efficiently extract machine-readable knowledge for training and testing purposes. A crucial aspect in ... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 14, 2024 Category: Bioinformatics Authors: Ornella Irrera, Stefano Marchesin and Gianmaria Silvello Tags: Software Source Type: research
StackDPP: a stacking ensemble based DNA-binding protein prediction model
DNA-binding proteins (DNA-BPs) are the proteins that bind and interact with DNA. DNA-BPs regulate and affect numerous biological processes, such as, transcription and DNA replication, repair, and organization ... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 14, 2024 Category: Bioinformatics Authors: Sheikh Hasib Ahmed, Dibyendu Brinto Bose, Rafi Khandoker and M Saifur Rahman Tags: Research Source Type: research
CREDO: a friendly Customizable, REproducible, DOcker file generator for bioinformatics applications
The analysis of large and complex biological datasets in bioinformatics poses a significant challenge to achieving reproducible research outcomes due to inconsistencies and the lack of standardization in the a... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 12, 2024 Category: Bioinformatics Authors: Simone Alessandri, Maria L. Ratto, Sergio Rabellino, Gabriele Piacenti, Sandro Gepiro Contaldo, Simone Pernice, Marco Beccuti, Raffaele A. Calogero and Luca Alessandri Tags: Software Source Type: research
Predicting lncRNA –protein interactions through deep learning framework employing multiple features and random forest algorithm
RNA-protein interaction (RPI) is crucial to the life processes of diverse organisms. Various researchers have identified RPI through long-term and high-cost biological experiments. Although numerous machine le... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 12, 2024 Category: Bioinformatics Authors: Ying Liang, XingRui Yin, YangSen Zhang, You Guo and YingLong Wang Tags: Research Source Type: research
Machine learning on alignment features for parent-of-origin classification of simulated hybrid RNA-seq
Parent-of-origin allele-specific gene expression (ASE) can be detected in interspecies hybrids by virtue of RNA sequence variants between the parental haplotypes. ASE is detectable by differential expression a... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 12, 2024 Category: Bioinformatics Authors: Jason R. Miller and Donald A. Adjeroh Tags: Research Source Type: research
DiseaseNet: a transfer learning approach to noncommunicable disease classification
As noncommunicable diseases (NCDs) pose a significant global health burden, identifying effective diagnostic and predictive markers for these diseases is of paramount importance. Epigenetic modifications, such... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 11, 2024 Category: Bioinformatics Authors: Steven Gore, Bailey Meche, Danyang Shao, Benjamin Ginnett, Kelly Zhou and Rajeev K. Azad Tags: Research Source Type: research
xCAPT5: protein –protein interaction prediction using deep and wide multi-kernel pooling convolutional neural networks with protein language model
Predicting protein –protein interactions (PPIs) from sequence data is a key challenge in computational biology. While various computational methods have been proposed, the utilization of sequence embeddings fro... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 10, 2024 Category: Bioinformatics Authors: Thanh Hai Dang and Tien Anh Vu Tags: Research Source Type: research
DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies
The prediction of cancer drug response is a challenging subject in modern personalized cancer therapy due to the uncertainty of drug efficacy and the heterogeneity of patients. It has been shown that the chara... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 9, 2024 Category: Bioinformatics Authors: Chuanqi Lao, Pengfei Zheng, Hongyang Chen, Qiao Liu, Feng An and Zhao Li Tags: Research Source Type: research
Bayesian inference for identifying tumour-specific cancer dependencies through integration of ex-vivo drug response assays and drug-protein profiling
The identification of tumor-specific molecular dependencies is essential for the development of effective cancer therapies. Genetic and chemical perturbations are powerful tools for discovering these dependenc... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 8, 2024 Category: Bioinformatics Authors: Hanwen Xing and Christopher Yau Tags: Research Source Type: research
Deep self-supervised machine learning algorithms with a novel feature elimination and selection approaches for blood test-based multi-dimensional health risks classification
Blood test is extensively performed for screening, diagnoses and surveillance purposes. Although it is possible to automatically evaluate the raw blood test data with the advanced deep self-supervised machine ... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 8, 2024 Category: Bioinformatics Authors: Onder Tutsoy and Gizem Gul Ko ç Tags: Research Source Type: research
Deepstacked-AVPs: predicting antiviral peptides using tri-segment evolutionary profile and word embedding based multi-perspective features with deep stacking model
Viral infections have been the main health issue in the last decade. Antiviral peptides (AVPs) are a subclass of antimicrobial peptides (AMPs) with substantial potential to protect the human body against vario... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - March 7, 2024 Category: Bioinformatics Authors: Shahid Akbar, Ali Raza and Quan Zou Tags: Research Source Type: research
