Deep Genomics Incorporated
Held is read from USPTO's recorded assignments; a transfer never recorded there does not appear.
Recorded under 2 name spellings.
0
Ending by 2030
Jan 2036
Next term end
When these terms end
Held patents by the year their term ends
20262027202820292030203120322033203420352036203720382039204020412042204320442045
Fee deadlines
Maintenance fees fall due 3.5, 7.5 and 11.5 years after grant. A missed fee ends a patent at the end of the six month grace period that follows, not on the due date.
- 1 fee due Dec 20, 2026The maintenance fee for System and Method for Training Neural Networks (US 11,681,917) comes due Dec 20, 2026. Unpaid by Jun 21, 2027, it lapses early.
- 2 fees due Mar 10 to 26, 2027 · next Mar 10
- 1 fee due Jul 30, 2027The maintenance fee for Systems and Methods for Classifying, Prioritizing and Interpreting Genetic Variants and Therapies Using a Deep Neural Network (US 11,887,696) comes due Jul 30, 2027. Unpaid by Jan 31, 2028, it lapses early.
Recent changes
Nothing was recorded against this company's patents in the last 90 days.
Patents held now
Soonest term end first. Each date below is computed on that patent's own page, which shows the rule, the adjustments and the fee history it was derived from.
| Patent | Title | Status | Expires | Confidence |
|---|---|---|---|---|
| US 10,185,803 | Systems and Methods for Classifying, Prioritizing and Interpreting Genetic Variants and Therapies Using a Deep Neural Network In force · High confidence | In force | High confidence | |
| US 10,885,435 | System and Method for Training Neural Networks In force · High confidence | In force | High confidence | |
| US 11,681,917 | System and Method for Training Neural Networks In force · High confidence | In force | High confidence | |
| US 11,183,271 | Neural network architectures for linking biological sequence variants based on molecular phenotype, and systems and methods therefor In force · From the USPTO record | In force | From the USPTO record | |
| US 10,410,118 | System and Method for Training Neural Networks In force · High confidence | In force | High confidence | |
| US 12,626,782 | Architectures for Training Neural Networks Using Biological Sequences, Conservation, and Molecular Phenotypes In force · High confidence | In force | High confidence | |
| US 11,568,960 | Neural network architectures for scoring and visualizing biological sequence variations using molecular phenotype, and systems and methods therefor In force · From the USPTO record | In force | From the USPTO record | |
| US 11,578,327 | Oligonucleotide therapy for Wilson disease In force · From the USPTO record | In force | From the USPTO record | |
| US 11,887,696 | Systems and Methods for Classifying, Prioritizing and Interpreting Genetic Variants and Therapies Using a Deep Neural Network In force · Medium confidence | In force | Medium confidence | |
| US 11,636,920 | Systems and Methods for Generating and Training Convolutional Neural Networks Using Biological Sequences and Relevance Scores Derived from Structural, Biochemical, Population and Evolutionary Data In force · High confidence | In force | High confidence |
Sources and methods
Compiled from the USPTO record, grants, published applications and recorded assignments, not yet reviewed by hand.
How this record was built
Computed patent terms end on the dates shown. Related patents and pending applications may cover overlapping subject matter.
Published applications
US patent applications published under this name that have not become patents. An application is published about eighteen months after its earliest filing; one that has not been published is in no public record.
1 abandoned · 7 no status recorded