User profiles for Sira Sriswasdi
Sira SriswasdiLecturer, Research Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok … Verified email at chula.ac.th Cited by 1603 |
[HTML][HTML] Federated learning for predicting clinical outcomes in patients with COVID-19
…, PMC e Silva, P Wang, S Xu, S Kawano, S Sriswasdi… - Nature medicine, 2021 - nature.com
Federated learning (FL) is a method used for training artificial intelligence models with data
from multiple sources while maintaining data anonymity, thus removing many barriers to data …
from multiple sources while maintaining data anonymity, thus removing many barriers to data …
[HTML][HTML] Generalist species drive microbial dispersion and evolution
Microbes form fundamental bases of every Earth ecosystem. As their key survival strategies,
some microbes adapt to broad ranges of environments, while others specialize to certain …
some microbes adapt to broad ranges of environments, while others specialize to certain …
Systematic discovery of ectopic pregnancy serum biomarkers using 3-D protein profiling coupled with label-free quantitation
LA Beer, HY Tang, S Sriswasdi… - Journal of proteome …, 2011 - ACS Publications
Ectopic pregnancy (EP) and normal intrauterine pregnancy (IUP) serum proteomes were
quantitatively compared to systematically identify candidate biomarkers. A 3-D biomarker …
quantitatively compared to systematically identify candidate biomarkers. A 3-D biomarker …
[HTML][HTML] Identification of Daboia siamensis venome using integrated multi-omics data
Snakebite, classified by World Health Organization as a neglected tropical disease, causes
more than 100,000 deaths and 2 million injuries per year. Currently, available antivenoms do …
more than 100,000 deaths and 2 million injuries per year. Currently, available antivenoms do …
[HTML][HTML] Federated Learning used for predicting outcomes in SARS-COV-2 patients
…, P Wang, S Xu, S Kawano, S Sriswasdi… - Research …, 2021 - ncbi.nlm.nih.gov
‘Federated Learning’(FL) is a method to train Artificial Intelligence (AI) models with data from
multiple sources while maintaining anonymity of the data thus removing many barriers to …
multiple sources while maintaining anonymity of the data thus removing many barriers to …
[HTML][HTML] MHCSeqNet: a deep neural network model for universal MHC binding prediction
Background Immunotherapy is an emerging approach in cancer treatment that activates the
host immune system to destroy cancer cells expressing unique peptide signatures (…
host immune system to destroy cancer cells expressing unique peptide signatures (…
[PDF][PDF] Epigenetic regulation of condensin-mediated genome organization during the cell cycle and upon DNA damage through histone H3 lysine 56 acetylation
A Tanaka, H Tanizawa, S Sriswasdi, O Iwasaki… - Molecular cell, 2012 - cell.com
Complex genome organizations participate in various nuclear processes including
transcription, DNA replication, and repair. However, the mechanisms that generate and regulate …
transcription, DNA replication, and repair. However, the mechanisms that generate and regulate …
[HTML][HTML] Uncovering thousands of new peptides with sequence-mask-search hybrid de novo peptide sequencing framework
…, DW Speicher, E Chuangsuwanich, S Sriswasdi - Molecular & Cellular …, 2019 - ASBMB
Typical analyses of mass spectrometry data only identify amino acid sequences that exist in
reference databases. This restricts the possibility of discovering new peptides such as those …
reference databases. This restricts the possibility of discovering new peptides such as those …
Deficit schizophrenia is a discrete diagnostic category defined by neuro-immune and neurocognitive features: results of supervised machine learning
B Kanchanatawan, S Sriswasdi, S Thika… - Metabolic brain …, 2018 - Springer
Deficit schizophrenia is characterized by neurocognitive impairments and changes in the
patterning of IgA/IgM responses to plasma tryptophan catabolites (TRYCATs). In the current …
patterning of IgA/IgM responses to plasma tryptophan catabolites (TRYCATs). In the current …
[HTML][HTML] An explainable self-attention deep neural network for detecting mild cognitive impairment using multi-input digital drawing tasks
…, S Teerapittayanon, S Sriswasdi… - Alzheimer's Research & …, 2022 - Springer
Background Mild cognitive impairment (MCI) is an early stage of cognitive decline which
could develop into dementia. An early detection of MCI is a crucial step for timely prevention …
could develop into dementia. An early detection of MCI is a crucial step for timely prevention …