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Analysis

1.WO/2025/137774METHOD OF GENERATING AND SCREENING PEPTIDE APTAMER LIBRARIES FROM NATURALLY OCCURRING PROTEINS
WO 03.07.2025
Int.Class G16B 40/10
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
40ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
10Signal processing, e.g. from mass spectrometry or from PCR
Appl.No PCT/CA2024/051737 Applicant MARSHALL, John G. Inventor MARSHALL, John G.
Provided herein are methods of making a peptide aptamer library from naturally occurring proteins and/or peptides. The peptide aptamer library can be generated from immunoglobulins, B cell receptors and/or T cell receptors of a host animal. Biological samples such as cells and biofluids can be used as a library of peptide aptamers. Also provided herein are methods to identify peptide aptamers that bind a target using the peptide aptamer library generated by the methods disclosed herein.
2.WO/2025/141959METHOD FOR PREDICTING PROMOTER ACTIVITY AND METHOD FOR MODIFYING PROMOTER BASED ON RESULTS OF PREDICTING PROMOTER ACTIVITY
WO 03.07.2025
Int.Class C12N 15/09
CCHEMISTRY; METALLURGY
12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
NMICROORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICROORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
15Mutation or genetic engineering; DNA or RNA concerning genetic engineering, vectors, e.g. plasmids, or their isolation, preparation or purification; Use of hosts therefor
09Recombinant DNA-technology
Appl.No PCT/JP2024/030592 Applicant GRA&GREEN INC. Inventor TOYOKURA Koichi
The present disclosure provides a method for obtaining a promoter sequence modified so as to have a desired transcriptional activity. More specifically, provided is a method for obtaining a promoter sequence modified so as to have a desired transcription activity, the method comprising: preparing an original promoter sequence to be modified; generating a set of a plurality of modified promoter sequences that can be created by genome editing techniques on the basis of the promoter sequence; predicting, by a machine learning model, the transcription activity of each modified promoter sequence included in the set of modified promoter sequences generated; and selecting a modified promoter sequence predicted to have a desired active transcription performance.
3.WO/2025/137775METHOD OF GENERATING AND SCREENING SYNTHETIC PEPTIDE APTAMER LIBRARIES
WO 03.07.2025
Int.Class C40B 30/04
CCHEMISTRY; METALLURGY
40COMBINATORIAL TECHNOLOGY
BCOMBINATORIAL CHEMISTRY; LIBRARIES, e.g. CHEMICAL LIBRARIES
30Methods of screening libraries
04by measuring the ability to specifically bind a target molecule, e.g. antibody-antigen binding, receptor-ligand binding
Appl.No PCT/CA2024/051738 Applicant MARSHALL, John G. Inventor MARSHALL, John G.
Provided herein are methods of making a peptide aptamer library of partially random peptide aptamers. The peptide aptamer library can be designed with tryptic and chymotryptic sites spaced to create domains. In each domain, a defined subset of amino acids are randomly ordered alongside invariant amino acids. Also provided herein are methods to identify peptide aptamers that bind a target using the peptide aptamer library disclosed herein.
4.WO/2025/138729BASE CALLING METHOD AND SYSTEM, ANALYSIS METHOD AND SYSTEM, AND ELECTRONIC DEVICE AND STORAGE MEDIUM
WO 03.07.2025
Int.Class G16B 20/30
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
20ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
30Detection of binding sites or motifs
Appl.No PCT/CN2024/106234 Applicant MGI TECH CO., LTD. Inventor HUANG, Fuxing
A base calling method and system, an analysis method and system, and an electronic device and a storage medium. The base calling method comprises: acquiring first light intensity data corresponding to each target pixel point in a target image under a set number of instances of test sequencing, wherein each target pixel point corresponds to a nucleic acid sequence cluster to be tested; on the basis of the first light intensity data, determining light intensity distribution intervals respectively corresponding to different types of bases; acquiring target light intensity data corresponding to each target pixel point in the target image under any instance of actual sequencing; and on the basis of the target light intensity data and the light intensity distribution intervals, obtaining a target base calling result under the instance of actual sequencing. Base calling can be implemented by using distributed computing, so that data transmission pressure and analysis pressure are reduced, and storage consumption is reduced; and the occurrence of luminescence unevenness caused by the efficiency of DNB rolling circle amplification is also reduced, thereby effectively improving the accuracy and processing efficiency of base calling.
5.WO/2025/144699LARGE LANGUAGE MODEL DRIVEN DATA AUGMENTATION FOR PROTEIN MACHINE LEARNING
WO 03.07.2025
Int.Class G16B 30/00
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
30ICT specially adapted for sequence analysis involving nucleotides or amino acids
Appl.No PCT/US2024/061228 Applicant X DEVELOPMENT LLC Inventor VAGGI, Federico
A method for training a machine learning model (MLM) to predict the activity of a protein is described herein. In an example, a method involves accessing a set of training data comprising labeled examples with known activity levels. A large language model is used to generate synthetic examples of each labeled example by incorporating each possible amino acid (AA) mutation at each AA position in the labeled example and predicting the probability each AA mutation has of replacing the original AA. Based on a predetermined cutoff, a subset of negative synthetic examples that comprises at least one AA mutation with the lowest probability of being incorporated are selected. An augmented training dataset is generated and a MLM is trained, using the training data and the augmented training data set, by performing iterative operations to find a set of parameters that jointly minimize the sum of at least two loss functions.
6.WO/2025/141506ALLELE-SPECIFIC COPY NUMBER DETECTION FROM LOW COVERAGE GENOTYPING DATA
WO 03.07.2025
Int.Class G16B 20/10
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
20ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
10Ploidy or copy number detection
Appl.No PCT/IB2024/063202 Applicant SOPHIA GENETICS S.A. Inventor POZZORINI, Christian
Provided is a computer-implemented method for characterization of a sample from low-coverage genotyping data, the method comprising obtaining a sequencing data from the sample; aligning the sequencing data obtained for the sample to the reference genome to generate a read alignment file; identifying at least one informative variant; for each of the at least one locus containing an informative variant from the read alignment file, computing NAlti, comprising: computing a number of reads supporting the presence of the variant, and computing a depth of sequencing at the locus; modeling, over each of the at least one genomic loci, according to a normalized coverage and an observed variant fraction, an allele-specific copy number for the at least one genomic loci; and outputting, for each of the at least one genomic loci, at least one of an absolute copy number or an allelic composition.
7.WO/2025/138253GENETIC VARIATION DETECTION METHOD AND APPARATUS, STORAGE MEDIUM, AND COMPUTER DEVICE
WO 03.07.2025
Int.Class G16B 20/20
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
20ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
20Allele or variant detection, e.g. single nucleotide polymorphism detection
Appl.No PCT/CN2023/143619 Applicant BGI SHENZHEN Inventor HE, Lei
Embodiments of the present application belong to the field of genetic variation detection, and provide a genetic variation detection method and apparatus, a storage medium, and a computer device. The method comprises: by means of a high-quality single-base variation site measured by a model for performing genetic variation detection on the basis of gene accumulation, determining, from a reference haplotype set, a haplotype of a gene segment under test, and, on the basis of the haplotype, determining an insertion/deletion site of the gene segment under test.
8.WO/2025/141058METHODS FOR IDENTIFYING HIGH AVIDITY T CELL RECEPTORS OR T CELLS
WO 03.07.2025
Int.Class G16B 15/20
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
15ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
20Protein or domain folding
Appl.No PCT/EP2024/088417 Applicant LUDWIG INSTITUTE FOR CANCER RESEARCH LTD Inventor ZOETE, Vincent
This disclosure describes methods for identifying a T cell receptor (TCR) with high avidity against an antigen or an immune cell comprising the TCR. The success of cancer immunotherapy depends in part on the strength of antigen recognition by T cells. Relative to tumor-associated antigen (TAA)-specific T cells, neoantigen-specific T cells were of higher structural avidity and, consistently, were preferentially detected in tumors. Effective tumor infiltration in mice models was associated with high structural avidity and CXCR3 expression. Based on TCRs biophysicochemical properties, an in silico model was developed and applied for predicting TCR structural avidity and validated the enrichment in high avidity T cells in patients' tumors. The results demonstrate a direct relationship between neoantigen recognition, T cell functionality, and tumor infiltration. Thus, the disclosed methods represent a rational approach to identify potent T cells for personalized cancer immunotherapy.
9.WO/2025/139021CODON OPTIMIZATION METHOD
WO 03.07.2025
Int.Class G16B 30/00
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
30ICT specially adapted for sequence analysis involving nucleotides or amino acids
Appl.No PCT/CN2024/116834 Applicant YUNZHOU BIOSCIENCES (GUANGZHOU) CO., LTD. Inventor MENG, Weineng
A codon optimization method is provided, which involves substituting codons on the basis of parameters such as the type and the number of codons, the local GC content, local repetitive sequences, mRNA secondary structures and the mRNA free energy; optimized sequences can be experimentally screened to obtain DNA sequences capable of high-level protein expression. The method is primarily applied downstream in the field of IVT mRNA: optimized DNA sequences are cloned into vectors and plasmid linearization is performed to form templates used for in-vitro transcription of mRNA, and the mRNA is encapsulated into LNPs or LNPs conjugated with other molecules, achieving a significant improvement in protein expression in 293T cells (not limited to 293T cells) or mice.
10.WO/2025/141151COMPUTER-IMPLEMENTED METHOD FOR ESTIMATING FRACTIONAL FLOW RESERVE AND SYSTEM
WO 03.07.2025
Int.Class G16B 40/20
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
40ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
20Supervised data analysis
Appl.No PCT/EP2024/088553 Applicant BIOME Inventor VELIKORODNYY, Alexey
The invention relates to a method for estimating the fractional flow reserve (FFR) of a vessel, including: - acquiring (ACQ1) a first image from an imaging system; - extracting (EXT1) a first data set (ENS1) defining anatomical descriptors of a first vessel; - acquiring (ACQ2) a second data set (ENS2) including at least the heart rate, the systolic pressure and the myocardial mass; and - generating (GEN1) an output (S1) defining a prediction of a fractional flow reserve (FFR) quantity by executing a first machine learning model (MLA1) to produce an output (S1), the first machine learning model (MLA1) implementing a parameterisable loss function including at least a first factor modelling at least one optimised parameterised physical constraint when training the model (MLA1), the parameterised physical constraint resulting in particular from a digital model of hemodynamic equations (MOD1).