JP7626466B2 - 情報処理装置、情報処理方法、情報処理プログラム、及び情報処理システム - Google Patents
情報処理装置、情報処理方法、情報処理プログラム、及び情報処理システム Download PDFInfo
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- JP7626466B2 JP7626466B2 JP2022108668A JP2022108668A JP7626466B2 JP 7626466 B2 JP7626466 B2 JP 7626466B2 JP 2022108668 A JP2022108668 A JP 2022108668A JP 2022108668 A JP2022108668 A JP 2022108668A JP 7626466 B2 JP7626466 B2 JP 7626466B2
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- G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2020189856 | 2020-11-13 | ||
| JP2020189856 | 2020-11-13 | ||
| JP2021023750A JP7125575B2 (ja) | 2020-11-13 | 2021-02-17 | 情報処理装置、情報処理方法、情報処理プログラム、及び情報処理システム |
Related Parent Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2021023750A Division JP7125575B2 (ja) | 2020-11-13 | 2021-02-17 | 情報処理装置、情報処理方法、情報処理プログラム、及び情報処理システム |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2022137148A JP2022137148A (ja) | 2022-09-21 |
| JP2022137148A5 JP2022137148A5 (enExample) | 2024-02-28 |
| JP7626466B2 true JP7626466B2 (ja) | 2025-02-04 |
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| Application Number | Title | Priority Date | Filing Date |
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| JP2022108668A Active JP7626466B2 (ja) | 2020-11-13 | 2022-07-05 | 情報処理装置、情報処理方法、情報処理プログラム、及び情報処理システム |
Country Status (4)
| Country | Link |
|---|---|
| US (1) | US12278001B2 (enExample) |
| EP (2) | EP4213158A1 (enExample) |
| JP (1) | JP7626466B2 (enExample) |
| CN (1) | CN114496093A (enExample) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US12587274B2 (en) | 2023-03-28 | 2026-03-24 | Quantum Generative Materials Llc | Satellite optimization management system based on natural language input and artificial intelligence |
| JP7586541B1 (ja) | 2023-10-02 | 2024-11-19 | 株式会社Preferred Elements | 情報処理装置及び情報処理システム |
| US12603701B2 (en) | 2023-12-27 | 2026-04-14 | Quantum Generative Materials Llc | Distributed satellite constellation management and control system |
| US12627372B2 (en) | 2023-12-27 | 2026-05-12 | Quantum Generative Materials Llc | Advanced mission control predictive systems for low earth orbit semi-autonomous satellites |
| US12368503B2 (en) | 2023-12-27 | 2025-07-22 | Quantum Generative Materials Llc | Intent-based satellite transmit management based on preexisting historical location and machine learning |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100121791A1 (en) | 2006-11-03 | 2010-05-13 | Insilicotech Co., Ltd. | System, method and program for pharmacokinetic parameter prediction of peptide sequence by mathematical model |
| US20150300968A1 (en) | 2012-12-05 | 2015-10-22 | Nymirum, Inc. | Device and Methods for Analysis of Biomolecule Structure, Dynamics and Activity |
| JP2019028879A (ja) | 2017-08-02 | 2019-02-21 | 学校法人立命館 | 結合性予測方法、装置、プログラム、記録媒体、および機械学習アルゴリズムの製造方法 |
| JP2019179356A (ja) | 2018-03-30 | 2019-10-17 | 株式会社エムティーアイ | エピトープ予測方法及びエピトープ予測システム |
Family Cites Families (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DK0974111T3 (da) * | 1997-04-11 | 2003-04-22 | California Inst Of Techn | Apparat og metode til automatiseret design af proteiner |
| AU3465701A (en) * | 2000-02-01 | 2001-08-14 | Ppd Discovery, Inc. | Data processing system for compound development programs |
| WO2003054743A1 (fr) | 2001-12-10 | 2003-07-03 | Fujitsu Limited | Appareil de prediction de la structure tridimensionnelle d'une proteine et procede de prediction associe |
| KR100924328B1 (ko) * | 2006-11-03 | 2009-11-02 | 주식회사 인실리코텍 | 수학적 모델을 이용한 펩타이드 서열의 약동학적 성질 예측시스템 및 방법과 그 프로그램을 저장한 기록매체 |
| EP3127921A1 (en) * | 2007-09-26 | 2017-02-08 | Chugai Seiyaku Kabushiki Kaisha | Method of modifying isoelectric point of antibody via amino acid substition in cdr |
| US20130080134A1 (en) * | 2008-07-25 | 2013-03-28 | Fundação D. Anna Sommer Champalimaud e Dr. Carlos Montez Champalimaud | Systems and methods for predicting favorable-risk disease for patients enrolled in active surveillance |
| JP5435539B2 (ja) * | 2008-09-29 | 2014-03-05 | 独立行政法人産業技術総合研究所 | 抗体産生細胞の活性化ペプチド |
| JP5098950B2 (ja) * | 2008-10-21 | 2012-12-12 | 株式会社島津製作所 | クライアント・サーバ型分析システム |
| JP6121456B2 (ja) | 2012-03-09 | 2017-04-26 | ビーエーエスエフ ソシエタス・ヨーロピアＢａｓｆ Ｓｅ | 窒素及びホウ素でドープされたグラフェンを原料とするエアロゲル |
| JP6311864B2 (ja) * | 2014-01-15 | 2018-04-18 | 株式会社コナミデジタルエンタテインメント | ゲーム制御装置、ゲーム制御システム、プログラム |
| JP6558754B2 (ja) | 2015-08-07 | 2019-08-14 | 富士通株式会社 | 情報処理装置、指標次元抽出方法、および指標次元抽出プログラム |
| WO2017214574A1 (en) * | 2016-06-10 | 2017-12-14 | Twist Bioscience Corporation | Systems and methods for automated annotation and screening of biological sequences |
| CN106167515A (zh) * | 2016-09-30 | 2016-11-30 | 南京英沛生物技术有限公司 | 一组Protegrin‑1抗菌肽衍生物及其制备方法与应用 |
| AU2018254526B2 (en) | 2017-04-19 | 2024-02-15 | Seattle Project Corp. | Neoantigen identification, manufacture, and use |
| CA3066635A1 (en) | 2017-06-09 | 2018-12-13 | Gritstone Oncology, Inc. | Neoantigen identification, manufacture, and use |
| JP6559850B1 (ja) * | 2018-07-27 | 2019-08-14 | Ｋａｒｙｄｏ ＴｈｅｒａｐｅｕｔｉＸ株式会社 | ヒトにおける被験物質の作用を予測するための人工知能モデル |
| US12431219B2 (en) * | 2019-04-15 | 2025-09-30 | Bruker Daltonics GmbH & Co. KG | Methods for determining isomeric amino acid residues of proteins and peptides |
| JP2022534072A (ja) * | 2019-05-23 | 2022-07-27 | 武田薬品工業株式会社 | 遺伝性血管性浮腫を、モデリング、シミュレーション、及び治療するための方法及び装置 |
| WO2020235665A1 (en) | 2019-05-23 | 2020-11-26 | Kaken Pharmaceutical Co., Ltd. | Crystalline form of sofpironium bromide and preparation method thereof |
| JP7423931B2 (ja) | 2019-08-09 | 2024-01-30 | 株式会社三洋物産 | 遊技機 |
| CN111363026B (zh) * | 2020-03-31 | 2022-03-25 | 浙江省中医院、浙江中医药大学附属第一医院（浙江省东方医院） | 一种增强抗原多肽亲和力和稳定性的方法 |
| US20210327553A1 (en) * | 2020-04-17 | 2021-10-21 | Cipherome, Inc. | Prediction of adverse drug reaction based on machine-learned models using protein function scores and clinical factors |
-
2021
- 2021-11-11 EP EP23160865.4A patent/EP4213158A1/en not_active Withdrawn
- 2021-11-11 EP EP21207727.5A patent/EP4002383A3/en active Pending
- 2021-11-12 US US17/524,758 patent/US12278001B2/en active Active
- 2021-11-12 CN CN202111341383.5A patent/CN114496093A/zh active Pending
-
2022
- 2022-07-05 JP JP2022108668A patent/JP7626466B2/ja active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100121791A1 (en) | 2006-11-03 | 2010-05-13 | Insilicotech Co., Ltd. | System, method and program for pharmacokinetic parameter prediction of peptide sequence by mathematical model |
| US20150300968A1 (en) | 2012-12-05 | 2015-10-22 | Nymirum, Inc. | Device and Methods for Analysis of Biomolecule Structure, Dynamics and Activity |
| JP2019028879A (ja) | 2017-08-02 | 2019-02-21 | 学校法人立命館 | 結合性予測方法、装置、プログラム、記録媒体、および機械学習アルゴリズムの製造方法 |
| JP2019179356A (ja) | 2018-03-30 | 2019-10-17 | 株式会社エムティーアイ | エピトープ予測方法及びエピトープ予測システム |
Also Published As
| Publication number | Publication date |
|---|---|
| US12278001B2 (en) | 2025-04-15 |
| US20220157407A1 (en) | 2022-05-19 |
| JP2022137148A (ja) | 2022-09-21 |
| EP4002383A3 (en) | 2022-08-03 |
| EP4213158A1 (en) | 2023-07-19 |
| CN114496093A (zh) | 2022-05-13 |
| EP4002383A2 (en) | 2022-05-25 |
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