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Results: 462
Investigating meta-approaches for reconstructing gene networks in a mammalian cellular context.
The output of state-of-the-art reverse-engineering methods for biological networks is often based on the fitting of a mathematical model to the data. Typically, different datasets do not give single consistent network...
PECLIDES Neuro
Neurodegenerative diseases such as Alzheimer's and Parkinson's impact millions of people worldwide. Early diagnosis has proven to greatly increase the chances of slowing down the diseases' progression. Correct diagnosis often...
DrugClust
Background: Identification of underlying mechanisms behind drugs side effects is of extreme interest and
importance in drugs discovery today. Therefore machine learning methodology, linking such different
multi features aspects...
A Fine-Grained IoT Data Access Control Scheme Combining Attribute-Based Encryption and Blockchain
IoT technology has been widely valued and applied, and the resulting massive IoT data brings many challenges to the traditional centralized data management, such as performance, privacy, and security challenges. This paper...
Distance-Based Opportunistic Mobile Data Offloading.
Cellular network data traffic can be offload onto opportunistic networks. This paper proposes a Distance-based Opportunistic Publish/Subscribe (DOPS) content dissemination model, which is composed of three layers: application...
Multi-omic analysis of signalling factors in inflammatory comorbidities.
BACKGROUND: Inflammation is a core element of many different, systemic and chronic diseases that usually involve an important autoimmune component. The clinical phase of inflammatory diseases is often the culmination of a long...
evolution Gene families Inflammation Multi–omic approach Comorbidity DNA Methylation Gene Expression Profiling Gene Expression Regulation Gene Regulatory Networks Genetic Association Studies Genomics Humans Inflammation Multigene Family Phylogeny principal component analysis Receptors Tumor Necrosis Factor Signal Transduction
XFlow
In recent years, there have been numerous developments toward solving multimodal tasks, aiming to learn a stronger representation than through a single modality. Certain aspects of the data can be particularly useful in this...
ML-SIM
Structured illumination microscopy (SIM) has become an important technique for
optical super-resolution imaging because it allows a doubling of image resolution at speeds
compatible with live-cell imaging. However, the...
Analyzing seasonality of tuberculosis across Indian states and union territories.
A significant seasonal variation in tuberculosis (TB) is observed in north India during 2006-2011, particularly in states like Himachal Pradesh, Haryana and Rajasthan. To quantify the seasonal variation, we measure average...
Single-cell RNA-sequencing uncovers transcriptional states and fate decisions in haematopoiesis.
Emmanouil I Athanasiadis, Jan G Botthof, Helena Andres, Lauren Ferreira, Pietro Lio, Ana Cvejic
Jun 19, 2018
Prediction by graph theoretic measures of structural effects in proteins arising from non-synonymous single nucleotide polymorphisms.
Recent analyses of human genome sequences have given rise to impressive advances in identifying non-synonymous single nucleotide polymorphisms (nsSNPs). By contrast, the annotation of nsSNPs and their links to diseases are...
Artificial Intelligence Computational Biology DNA Mutational Analysis Genetic Predisposition to Disease Humans Models Genetic Models Molecular Neural Networks Computer Polymorphism Single Nucleotide Predictive Value of Tests Protein Conformation Protein Interaction Mapping Proteins Sequence Alignment Sequence Analysis Protein Thermodynamics
iBitter-Fuse
Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, Mohammad Ali Moni, Pietro Lio', Watshara Shoombuatong
Nov 05, 2021
Accurate identification of bitter peptides is of great importance for better understanding their biochemical and biophysical properties. To date, machine learning-based methods have become effective approaches for providing a...
Intra- and inter-chromosomal interactions correlate with CTCF binding genome wide.
A prime goal in systems biology is the comprehensive use of existing high-throughput genomic datasets to gain a better understanding of chromatin organization and genome function. In this report, we use chromatin...
ML-SIM
Structured illumination microscopy (SIM) has become an important technique for optical super-resolution imaging because it allows a doubling of image resolution at speeds compatible with live-cell imaging. However, the...
Published by: Biomedical optics express
Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis.
Sarinder Kaur Dhillon, Mogana Darshini Ganggayah, Siamala Sinnadurai, Pietro Lio, Nur Aishah Taib
Nov 04, 2022
Predicting factors for survival of breast cancer patients using machine learning techniques.
Mogana Darshini Ganggayah, Nur Aishah Taib, Yip Cheng Har, Pietro Lio, Sarinder Kaur Dhillon
Apr 05, 2019
iBitter-Fuse
Phasit Charoenkwan, Chanin Nantasenamat, Md Mehedi Hasan, Mohammad Ali Moni, Pietro Lio', Watshara Shoombuatong
Sep 27, 2021
classification Bioinformatics Support Vector Machine Feature selection Machine Learning bitter peptide Humans Peptide Fragments Predictive Value of Tests Taste Algorithms Software Benchmarking Support Vector Machine
Published by: International journal of molecular sciences
iBitter-Fuse
Phasit Charoenkwan, Chanin Nantasenamat, Md. Mehedi Hasan, Mohammad Ali Moni, Pietro Lio’, Watshara Shoombuatong
Aug 26, 2021
Accurate identification of bitter peptides is of great importance for better understanding their biochemical and biophysical properties. To date, machine learning-based methods have become effective approaches for providing a...
Global gene expression profiling and senescence biomarker analysis of hESC exposed to H2O2 induced non-cytotoxic oxidative stress.
Maria Barandalla, Hui Shi, Hui Xiao, Silvia Colleoni, Cesare Galli, Pietro Lio, Matthew Trotter, Giovanna Lazzari
Aug 21, 2017
BACKGROUND: Human embryonic stem cells (hESCs) potentially offer new routes to study, on the basis of the Developmental Origins of Health and Disease (DOHaD) concept, how the maternal environment during pregnancy influences the...
SCMTHP
Phasit Charoenkwan, Wararat Chiangjong, Chanin Nantasenamat, Mohammad Ali Moni, Pietro Lio', Balachandran Manavalan, Watshara Shoombuatong
Feb 21, 2022
Tumor-homing peptides (THPs) are small peptides that can recognize and bind cancer cells specifically. To gain a better understanding of THPs' functional mechanisms, the accurate identification and characterization of THPs is...
AMYPred-FRL is a novel approach for accurate prediction of amyloid proteins by using feature representation learning.
Phasit Charoenkwan, Saeed Ahmed, Chanin Nantasenamat, Julian MW Quinn, Mohammad Ali Moni, Pietro Lio', Watshara Shoombuatong
May 11, 2022
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