
생물정보학은 대규모 유전체, 전사체, 단백체 및 대사체 데이터 세트를 분석하고 해석하기 위해 계산 방법과 통계 기법을 통합합니다. 이 분야는 서열 정렬, 게놈 조립, 유전자 발현 프로파일링, 단백질 구조 예측 및 분자 상호작용 네트워크를 다루며, 분자 기능, 진화적 관계 및 질병 메커니즘에 대한 통찰력을 제공합니다. 알고리즘 개발, 머신러닝 응용 프로그램 및 고처리량 데이터 처리의 발전은 포괄적인 주석, 변이 해석 및 시스템 수준 모델링을 가능하게 합니다. 다음 모음집은 생물학 연구 및 정밀 의학 발전에 필수적인 계산 도구, 데이터베이스 관리, 분석 파이프라인 및 통합적 접근 방식에 초점을 맞춘 최신 과학 논문과 특허 혁신 기술을 정리한 것입니다.
본 자료는 전 세계 과학 온라인 저널에 게재된 영문 생물정보학 관련 최신 논문 및 특허를 엄선하여 정리한 것으로, 유전체 서열, 서열 정렬, 단백질 구조 예측, 계통 발생, 유전자 발현, 차세대 시퀀싱, 생물정보학, 전산 유전체학, 전사체학, 메타유전체학, 단백체학 데이터 분석, 분자 도킹, 생물학 데이터베이스, 구조 생물정보학, 유전체 주석, 변이 검출, 후성유전체학, 시스템 생물학, 비교 유전체학, 기능 유전체학, RNA-Seq 분석, 생물통계학, 전산 생물학, 바이오마커 발굴, 경로 분석 및 대사체학 등을 주제로 분류 및 집중 분석했습니다.
Regulatory nucleic acid molecules for enhancing gene expression in plants
Patent published on the 2026-06-04 in WO under Ref WO2026114881 by BASF SE [DE] (Meulewaeter Frank [be], Davis Erin [be])
Abstract: The current disclosure generally relates to the technical field of plant molecular biology and provides methods for the production of high expressing promoters and the production of plants with enhanced expression of nucleic acids wherein one or more nucleic acid expression enhancing nucleic acid (NEENA) is functionally linked to said promoters and/or introduced into plants.[...]
Our summary: This disclosure focuses on enhancing gene expression in plants using regulatory nucleic acid molecules. It details methods for producing high-expressing promoters. The approach involves linking nucleic acid expression enhancing nucleic acids to these promoters in plants.
nucleic acid, gene expression, plant molecular biology, promoters
Patent
Aptamer specifically binding to cell-derived extracellular vesicles and method for discovering extracellular vesicle-specific biomarker using same
Patent published on the 2026-06-04 in WO under Ref WO2026117034 by KONKUK UNIV INDUSTRY ACADEMY COOPERATION FOUNDATION [KR] (Park Ki Soo [kr], Lee Eun Sung [kr], Jun Jimin [kr], Cha Byung Seok [kr], Kim Junhyeong [kr])
Abstract: The present invention relates to an aptamer specifically binding to cell-derived extracellular vesicles and a method for discovering an extracellular vesicle-specific biomarker using same. Specifically, the present invention relates to an aptamer specifically binding to cancer cell-derived extracellular vesicles, and a method for discovering an extracellular vesicle-specific biomarker using same. Unlike prior art requiring immobilization, a method for selecting an aptamer specifically binding to[...]
Our summary: The invention presents an aptamer that binds specifically to cancer cell-derived extracellular vesicles. It includes a method for discovering extracellular vesicle-specific biomarkers without immobilization, maintaining the three-dimensional structure. This approach facilitates novel biomarker discovery and target protein verification for diagnosis and drug development.
Aptamer, extracellular vesicles, biomarker discovery, cancer
Patent
Rhamnolipids for modified gene expression during wound healing
Patent published on the 2026-06-04 in WO under Ref WO2026117688 by STEPAN CO [US] (Strout Kelly [us], Savanhu Faith [us], Sanders Mitch [us])
Abstract: The technology presented herein, in general, relates to the use of biosurfactants, such as rhamnolipids, for treating and/or accelerating the healing of wounds. More particularly, the present technology relates to a method for treating chronic and acute wounds, by applying a composition comprising a mixture of rhamnolipids to the wound, wherein application of the composition facilitates coordinated gene expression associated with wound healing.[...]
Our summary: Rhamnolipids are used to enhance gene expression during wound healing. The method involves applying a rhamnolipid composition to wounds. This approach aims to treat both chronic and acute wounds effectively.
Rhamnolipids, biosurfactants, gene expression, wound healing
Patent
Prediction of stage and survival using isoform expression in gastric adenocarcinoma
Patent published on the 2026-06-04 in US under Ref US20260155253 by UNIV OF SOUTH FLORIDA [US] (Kuo Paul [us], Liang Yifan [us], Lien Kyle [us])
Abstract: Various processes, methods and systems are provided herein for assisting patients, medical providers and other personnel in predicting cancer stage and cancer survival. The systems and methods include determining an indication of a preliminary cancer diagnosis of a given type of cancer for a patient, receiving results of transcriptional sequencing analysis, extracting a set of isoform expression information from transcriptomic data, processing a cancer stemness isoform dataset for a patient, and[...]
Our summary: The content discusses methods for predicting cancer stage and survival in gastric adenocarcinoma using isoform expression. It involves analyzing transcriptional sequencing data and extracting relevant isoform information. The goal is to assist patients and medical providers in making informed decisions based on cancer diagnosis.
isoform expression, gastric adenocarcinoma, cancer prediction, transcriptomic data
Patent
Galnac oligonucleotide conjugate for inhibiting c5 gene expression
Patent published on the 2026-05-28 in WO under Ref WO2026108942 by CSPC ZHONGQI PHARMACEUTICAL TECH SHIJIAZHUANG CO LTD [CN] (Zhang Xueyan [cn], Wang Lingyu [cn], Su Xiaoye [cn], Zhao Chenglong [cn])
Abstract: Provided are an oligonucleotide conjugate comprising a GalNAc derivative, a pharmaceutical composition comprising the oligonucleotide conjugate, and use of the oligonucleotide conjugate or the pharmaceutical composition.[...]
Our summary: The content discusses a GalNAc oligonucleotide conjugate designed to inhibit C5 gene expression. It includes details about the conjugate, its pharmaceutical composition, and its applications. The focus is on the development and use of this therapeutic approach.
GalNAc, oligonucleotide, gene expression, pharmaceutical composition
Patent
Products and methods for full-length smchd1 expression using split inteins
Patent published on the 2026-05-21 in WO under Ref WO2026107323 by RESEARCH INST AT NATIONWIDE CHILDRENS HOSPITAL [US] (Harper Scott Q [us], Thangaraj Merlin Premalatha [us])
Abstract: Nucleic acids, vectors, compositions, systems, and methods for expressing a structural maintenance of chromosomes hinge domain containing 1 (SMCHD1) polypeptide to epigenetically silence double homeobox 4 (DUX4) for the treatment of a disease or disorder associated with DUX4 are provided. DUX4 regulates gene expression and plays a role in development, muscular dystrophy (including, but not limited to, facioscapulohumeral dystrophy (FSHD)), a cancer, or Bosma arhinia microphthalmia syndrome (BAMS[...]
Our summary: This content discusses products and methods for expressing the SMCHD1 polypeptide using split inteins. It highlights the role of DUX4 in diseases like muscular dystrophy and cancer. The approach aims to downregulate DUX4 expression for therapeutic purposes.
SMCHD1, split inteins, gene expression, DUX4
Patent
ReaxFF molecular dynamics investigation of co-combustion between Zhundong coal and lignin
Published on 2026-02-25 by @OXFORD
Abstract: AbstractCo-combustion of coal and biomass offers a promising solution to reduce fossil fuel dependency. This study employs reactive force-field molecular dynamics (ReaxFF MD) to investigate the microscopic effects of temperature and mixing ratio on Zhundong coal–lignin co-combustion. Elevated temperatures significantly enhance the conversion from large molecules to smaller gaseous products (CO2, H2O), suppressing tar formation. Higher coal ratios (3:1, 2:1) favor reduced tar yield and increase[...]
Our summary: This study uses ReaxFF molecular dynamics to analyze the co-combustion of Zhundong coal and lignin. Elevated temperatures and higher coal ratios improve gaseous product yields while reducing tar formation. Reaction pathways indicate distinct contributions from coal oxidation, lignin pyrolysis, and the behavior of nitrogen and sulfur during combustion.
ReaxFF, molecular dynamics, co-combustion, Zhundong coal
Publication
A Comparative Study of CNN, BiLSTM, and GRU Architectures
Published on 2026-02-03 by Elias Tabane, Ernest Mnkandla, Zenghui Wang @MDPI
Abstract: DNA sequence classification is a fundamental problem in bioinformatics, playing an indispensable role in gene annotation and disease prediction. Whereas most deep learning models, such as CNNs, BiLSTM networks, and GRUs, have been found individually optimal, each of these methods excels in modeling a specific aspect of sequence data: local motifs, long-range dependencies, and efficient temporal modeling of the sequences. Here, we present and evaluate an ensemble model that integrates CNN, BiLSTM[...]
Our summary: This study evaluates CNN, BiLSTM, and GRU architectures for DNA sequence classification. An ensemble model combining these methods achieved a classification accuracy of 90.6%, outperforming individual models. The research highlights the effectiveness of hybrid deep learning in genomic data analysis.
CNN, BiLSTM, GRU, ensemble
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