Alok Sharma 研究室

主宰者：Alok Sharma

東京大学

兼任：理化学研究所・RIKEN Center for Integrative Medical Sciences

AI 要約（直近 5 年の研究成果）

Alok Sharma研究室は、生物学的データの解析と予測を目的とした機械学習・深層学習の開発を中心に研究を行っています。研究室では、タンパク質の機能や構造に関する複雑なパターンを計算モデルで検出することに取り組んでいます。具体的には、タンパク質内における様々な化学修飾（リン酸化やメチル化など）が起きる位置の予測、タンパク質同士が相互作用する部位の同定、および単一細胞レベルでの遺伝子発現データから免疫細胞の種類を自動判定するなど、生物医学的に重要な問題に対して深層学習モデルを適用しています。これらの研究では、タンパク質の1次配列情報や立体構造情報、進化的背景を反映した特徴量を組み合わせることで、予測精度を向上させています。さらに研究室は、遺伝子発現データや表形式のデータセットなど、異なる形式のバイオデータを複数の視点から表現し直すことで、機械学習モデルがより詳細な情報を捉えられるよう工夫しています。これらの計算手法は、実験的に得ることが困難で時間と費用がかかる生物学的情報を迅速かつ安価に予測することを可能にし、医療応用や創薬研究への貢献を目指しています。

※ AI（Claude）が、公開されている論文要旨から研究の問い・手法・主要な発見を事実情報として抽出・再構成して自動生成しています。誤りを含む可能性があるため、正確性は研究室公式情報でご確認ください。

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研究成果（91 件）

[2025] Clinical Profile of Kidney Biopsies in Patients with Type 2 Diabetes and Role of Electron Microscopy
DOI: https://doi.org/10.1681/asn.2025xs1v4bkq
[2025] Clinical Profile of Kidney Biopsies in Patients with Type 2 Diabetes and Role of Electron Microscopy
DOI: https://doi.org/10.1681/asn.2025xs1v4bkq
[2025] CNN-Meth: A Tool to Accurately Predict Lysine Methylation Sites Using Evolutionary Information-Based Protein Modeling
DOI: https://doi.org/10.1007/978-1-0716-4623-6_11
[2025] Exploring Traditional uses, phytochemistry, pharmacology and future prospectives of Santalum album
DOI: https://doi.org/10.52783/jns.v14.1801
[2025] ProtCB-bind: Protein-carbohydrate binding site prediction using an ensemble of classifiers
DOI: https://doi.org/10.1016/j.carres.2025.109453
[2025] Lipofuscin Deposition in the Kidney: Damaging or Deceiving? - A Case Report
DOI: https://doi.org/10.25259/ijn_101_2025
[2025] Drug Repurposing: An Effective Strategy to Discover Treatments for MPOX
DOI: https://doi.org/10.2174/0122113525368527250719143915
[2025] scHDeepInsight: a hierarchical deep learning framework for precise immune cell annotation in single-cell RNA-seq data
DOI: https://doi.org/10.1093/bib/bbaf523
[2025] An ensemble-based model comprising deep learning for predicting peptide-binding residues in proteins
DOI: https://doi.org/10.1093/nargab/lqaf137
[2024] <scp>DeepPhoPred</scp> : Accurate Deep Learning Model to Predict Microbial Phosphorylation
DOI: https://doi.org/10.1002/prot.26734

続きを表示（残り 81 件）

[2024] Predicting lysine methylation sites using a convolutional neural network
DOI: https://doi.org/10.1016/j.ymeth.2024.04.007
[2024] SleepBoost: a multi-level tree-based ensemble model for automatic sleep stage classification
DOI: https://doi.org/10.1007/s11517-024-03096-x
[2024] Enhanced analysis of tabular data through Multi-representation DeepInsight
DOI: https://doi.org/10.1038/s41598-024-63630-7
[2024] Hypothyroidism Related Kidney Disease - A Report of Two Cases
DOI: https://doi.org/10.25259/ijn_266_2024
[2024] Metastatic Calcification in Allograft Kidney Due to Persistent Secondary Hyperparathyroidism: A Rare Cause of Graft Dysfunction.
DOI: https://doi.org/10.6002/ect.2024.0116
[2024] <scp>DeepPhoPred</scp> : Accurate Deep Learning Model to Predict Microbial Phosphorylation
DOI: https://doi.org/10.1002/prot.26734
[2024] Insight into Metabolomic Profiling of Tinospora cordifolia: Recent Advances and Future Perspectives of Quality Control
DOI: https://doi.org/10.4103/wjtcm.wjtcm_35_23
[2024] Insight into Metabolomic Profiling of Tinospora cordifolia: Recent Advances and Future Perspectives of Quality Control
DOI: https://doi.org/10.4103/wjtcm.wjtcm_35_23
[2024] Predicting lysine methylation sites using a convolutional neural network
DOI: https://doi.org/10.1016/j.ymeth.2024.04.007
[2024] SleepBoost: a multi-level tree-based ensemble model for automatic sleep stage classification
DOI: https://doi.org/10.1007/s11517-024-03096-x
[2024] Enhanced analysis of tabular data through Multi-representation DeepInsight
DOI: https://doi.org/10.1038/s41598-024-63630-7
[2024] Hypothyroidism Related Kidney Disease - A Report of Two Cases
DOI: https://doi.org/10.25259/ijn_266_2024
[2024] Metastatic Calcification in Allograft Kidney Due to Persistent Secondary Hyperparathyroidism: A Rare Cause of Graft Dysfunction.
DOI: https://doi.org/10.6002/ect.2024.0116
[2023] Changing Trends Towards Herbal Supplements: An Insight into Safetyand Herb-drug Interaction
DOI: https://doi.org/10.2174/1389201024666230718114606
[2023] PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features
DOI: https://doi.org/10.1038/s41598-023-47624-5
[2023] Post COVID-19 AA amyloidosis of the kidneys with rapidly progressive renal failure
DOI: https://doi.org/10.1080/19336896.2023.2201151
[2023] Cloud Computing: Algorithmic Appraisal by Response Time
DOI: https://doi.org/10.1109/smart59791.2023.10428626
[2023] Evaluation and Standardisation of Ayurvedic Lepa - A Traditional Lepa Chikitsa Therapy: An Ayurveda Cosmetology from Traditional to Modern Perspective
DOI: https://doi.org/10.2174/0122150838226522231113073535
[2023] Predicting Phosphoglycerylation with Transformer Features and Deep Learning
DOI: https://doi.org/10.1109/csde59766.2023.10487711
[2023] Vitamins strategies for psoriasis: An update on current scientific evidence
DOI: https://doi.org/10.1016/j.jhip.2024.01.005
[2023] Cloud Computing: Algorithmic Appraisal by Response Time
DOI: https://doi.org/10.1109/smart59791.2023.10428626
[2023] Evaluation and Standardisation of Ayurvedic Lepa - A Traditional Lepa Chikitsa Therapy: An Ayurveda Cosmetology from Traditional to Modern Perspective
DOI: https://doi.org/10.2174/0122150838226522231113073535
[2023] Predicting Phosphoglycerylation with Transformer Features and Deep Learning
DOI: https://doi.org/10.1109/csde59766.2023.10487711
[2023] Vitamins strategies for psoriasis: An update on current scientific evidence
DOI: https://doi.org/10.1016/j.jhip.2024.01.005
[2023] PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features
DOI: https://doi.org/10.1038/s41598-023-47624-5
[2023] Multimodal Depression Detection System Using Machine Learning
DOI: https://doi.org/10.1109/ici60088.2023.10421362
[2023] Memory capacity of recurrent neural networks with matrix representation
DOI: https://doi.org/10.1016/j.neucom.2023.126824
[2023] CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins
DOI: https://doi.org/10.1093/nar/gkad430
[2023] Multimodal Depression Detection System Using Machine Learning
DOI: https://doi.org/10.1109/ici60088.2023.10421362
[2023] Memory capacity of recurrent neural networks with matrix representation
DOI: https://doi.org/10.1016/j.neucom.2023.126824
[2023] Changing Trends Towards Herbal Supplements: An Insight into Safetyand Herb-drug Interaction
DOI: https://doi.org/10.2174/1389201024666230718114606
[2023] scDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning
DOI: https://doi.org/10.1093/bib/bbad266
[2023] Abstract A033: KRAS codon 12 oncogenic mutations modulate protein conformation within the Switch II/Helix3 pocket
DOI: https://doi.org/10.1158/1557-3125.ras23-a033
[2023] scDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning
DOI: https://doi.org/10.1093/bib/bbad266
[2023] CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins
DOI: https://doi.org/10.1093/nar/gkad430
[2023] Abstract A033: KRAS codon 12 oncogenic mutations modulate protein conformation within the Switch II/Helix3 pocket
DOI: https://doi.org/10.1158/1557-3125.ras23-a033
[2023] Post COVID-19 AA amyloidosis of the kidneys with rapidly progressive renal failure
DOI: https://doi.org/10.1080/19336896.2023.2201151
[2023] DeepInsight-3D architecture for anti-cancer drug response prediction with deep-learning on multi-omics
DOI: https://doi.org/10.1038/s41598-023-29644-3
[2023] Impact of Regional Quality Assessment of Tinospora cordifolia: A Scientific Perspective for Exploration of Harvest Strategy as a Quality Marker
DOI: https://doi.org/10.1007/s40003-022-00645-4
[2023] DeepInsight-3D architecture for anti-cancer drug response prediction with deep-learning on multi-omics
DOI: https://doi.org/10.1038/s41598-023-29644-3
[2023] Impact of Regional Quality Assessment of Tinospora cordifolia: A Scientific Perspective for Exploration of Harvest Strategy as a Quality Marker
DOI: https://doi.org/10.1007/s40003-022-00645-4
[2023] Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers
DOI: https://doi.org/10.1016/j.imu.2023.101348
[2023] Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers
DOI: https://doi.org/10.1016/j.imu.2023.101348
[2022] Potential of Essential Oils as Alternative Permeation Enhancers for Transdermal Delivery
DOI: https://doi.org/10.4103/2311-8571.351508
[2022] Q-Marker: An Integrative Approach and Scientific Validation in the Indian System of Medicine
DOI: https://doi.org/10.2174/2215083808666220831111344
[2022] OSPF Best Path Selection Manipulation using Reference Bandwidth
DOI: https://doi.org/10.5120/ijca2022922269
[2022] CNN-Pred: Prediction of single-stranded and double-stranded DNA-binding protein using convolutional neural networks
DOI: https://doi.org/10.1016/j.gene.2022.147045
[2022] Automatic Detection of Rice Diseases using Deep Convolutional Neural Networks with SGD and ADAM
DOI: https://doi.org/10.1109/icac3n56670.2022.10074538
[2022] CNN-Pred: Prediction of single-stranded and double-stranded DNA-binding protein using convolutional neural networks
DOI: https://doi.org/10.1016/j.gene.2022.147045
[2022] OSPF Default Cost Variation for Type-1 and Type-2 External Links during Redistribution
DOI: https://doi.org/10.5120/ijca2022922345
[2022] Potential of Essential Oils as Alternative Permeation Enhancers for Transdermal Delivery
DOI: https://doi.org/10.4103/2311-8571.351508
[2022] Q-Marker: An Integrative Approach and Scientific Validation in the Indian System of Medicine
DOI: https://doi.org/10.2174/2215083808666220831111344
[2022] OSPF Default Cost Variation for Type-1 and Type-2 External Links during Redistribution
DOI: https://doi.org/10.5120/ijca2022922345
[2022] Automatic Detection of Rice Diseases using Deep Convolutional Neural Networks with SGD and ADAM
DOI: https://doi.org/10.1109/icac3n56670.2022.10074538
[2022] iProtGly-SS: A Tool to Accurately Predict Protein Glycation Site Using Structural-Based Features
DOI: https://doi.org/10.1007/978-1-0716-2317-6_5
[2022] Phytochemical and Pharmacological Overview of Triticum aestivum: AnUpdate
DOI: https://doi.org/10.2174/2215083808666220428135532
[2022] iProtGly-SS: A Tool to Accurately Predict Protein Glycation Site Using Structural-Based Features
DOI: https://doi.org/10.1007/978-1-0716-2317-6_5
[2022] Phytochemical and Pharmacological Overview of Triticum aestivum: AnUpdate
DOI: https://doi.org/10.2174/2215083808666220428135532
[2022] An Insight into the Functional Benefit of Phenolic Acids from WholeGrains: An Update
DOI: https://doi.org/10.2174/1573401318666220610212537
[2022] An Insight into the Functional Benefit of Phenolic Acids from WholeGrains: An Update
DOI: https://doi.org/10.2174/1573401318666220610212537
[2022] A convolutional neural network based tool for predicting protein AMPylation sites from binary profile representation
DOI: https://doi.org/10.1038/s41598-022-15403-3
[2022] A convolutional neural network based tool for predicting protein AMPylation sites from binary profile representation
DOI: https://doi.org/10.1038/s41598-022-15403-3
[2022] OSPF Best Path Selection Manipulation using Reference Bandwidth
DOI: https://doi.org/10.5120/ijca2022922269
[2021] CluSem: Accurate clustering-based ensemble method to predict motor imagery tasks from multi-channel EEG data
DOI: https://doi.org/10.1016/j.jneumeth.2021.109373
[2021] ACP-MHCNN: an accurate multi-headed deep-convolutional neural network to predict anticancer peptides
DOI: https://doi.org/10.1038/s41598-021-02703-3
[2021] Performance Assessment of Gravity Retaining Wall with Rubber Tyre Waste mixed in dry cohesionless Backfill
DOI: https://doi.org/10.17509/ajse.v2i1.37272
[2021] DeepFeature: feature selection in nonimage data using convolutional neural network
DOI: https://doi.org/10.1093/bib/bbab297
[2021] CluSem: Accurate clustering-based ensemble method to predict motor imagery tasks from multi-channel EEG data
DOI: https://doi.org/10.1016/j.jneumeth.2021.109373
[2021] ACP-MHCNN: an accurate multi-headed deep-convolutional neural network to predict anticancer peptides
DOI: https://doi.org/10.1038/s41598-021-02703-3
[2021] DeepFeature: feature selection in nonimage data using convolutional neural network
DOI: https://doi.org/10.1093/bib/bbab297
[2021] Forecasting the spread of COVID-19 using LSTM network
DOI: https://doi.org/10.1186/s12859-021-04224-2
[2021] SPECTRA: a tool for enhanced brain wave signal recognition
DOI: https://doi.org/10.1186/s12859-021-04091-x
[2021] Flood Risk Maping using GSI and Flood Management analysis
[2021] Critical assessment of protein intrinsic disorder prediction
DOI: https://doi.org/10.1038/s41592-021-01117-3
[2021] SPECTRA: a tool for enhanced brain wave signal recognition
DOI: https://doi.org/10.1186/s12859-021-04091-x
[2021] Flood Risk Maping using GSI and Flood Management analysis
[2021] Critical assessment of protein intrinsic disorder prediction
DOI: https://doi.org/10.1038/s41592-021-01117-3
[2021] OPTICAL+: a frequency-based deep learning scheme for recognizing brain wave signals
DOI: https://doi.org/10.7717/peerj-cs.375
[2021] OPTICAL+: a frequency-based deep learning scheme for recognizing brain wave signals
DOI: https://doi.org/10.7717/peerj-cs.375
[2021] Forecasting the spread of COVID-19 using LSTM network
DOI: https://doi.org/10.1186/s12859-021-04224-2
[2021] Performance Assessment of Gravity Retaining Wall with Rubber Tyre Waste mixed in dry cohesionless Backfill
DOI: https://doi.org/10.17509/ajse.v2i1.37272

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AI 要約（直近 5 年の研究成果）

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