In the newly released version of Genomenal 1.7.1 you can:

• upload and analyze samples in batches (e.g. a sequencing run);
• create and customize clinical reports;
• administrate users of your organization (add new users, alter computational quotes, etc.).

Details:

Genomenal users often need to analyse genomes in groups or batches. These groups for example, can belong to a single sequencing run (although may be related due to other reasons), hence termed “runs”. Samples of a run can be uploaded faster than one by one avoiding necessity of registering separate samples or patients. Additionally, run samples can be viewed in Variant Viewer simultaneously speeding up the analysis process. This speed up is important in some settings, e.g. for oncology specialists, when time is a crucial factor.

We also developed manager of clinical reports. Users can create custom templates of reports reflecting neccessities of the clinical practice and focusing on high priority findings. User can customize content and the order of report blocks. Customized blocks can include variants specified by user-provided creteria, chromosomal aberrations, clinical recommendations and clinical trials.

Organization clients now have the ability manage its users. In administrator panel one can set user roles, set computational quotes and max size of the samples and invite new users with personalized configurational presets. Numerous improvements on bioinformatics side, documentation and UX/UI were also deployed.

BMC Medical Genomics published an article « RNAseq analysis of treatment-dependent signaling changes during inflammation in a mouse cutaneous wound healing model» with co-authorship of Novel (AcademGene) employees.

Despite proven therapeutic effects in inflammatory conditions, the specific mechanisms of phytochemical therapies are not well understood. The transcriptome effects of Traumeel (Tr14), a multicomponent natural product, and diclofenac, a non-selective cyclooxygenase (COX) inhibitor, were compared in a mouse cutaneous wound healing model to identify both known and novel pathways for the anti-inflammatory effect of plant-derived natural products.

The study interrogates a high-resolution map of the mouse transcriptome during wound healing to define changes resulting from therapeutic intervention with Traumeel (Tr14), a well-known natural multicomponent anti-inflammatory medicinal product for musculoskeletal conditions. The present studies were conducted to compare and explore more specifically the antiinflammatory effects of Tr14 and diclofenac at the transcriptome level.

Methods: Skin samples from abraded mice were analyzed by single-molecule, amplification-free RNAseq transcript profiling at 7 points between 12 and 192 h after injury. Immediately after injury, the wounds were treated with either diclofenac, Tr14, or placebo control (n = 7 per group/time). RNAseq levels were compared between treatment and control at each time point using a systems biology approach. Results: At early time points (12–36 h), both control and Tr14-treated wounds showed marked increase in the inducible COX2 enzyme mRNA, while diclofenac-treated wounds did not. Tr14, in contrast, modulated lipoxygenase transcripts, especially ALOX12/15, and phospholipases involved in arachidonate metabolism. Notably, Tr14 modulated a group of cell-type specific markers, including the T cell receptor, that could be explained by an overarching effect on the type of cells that were recruited into the wound tissue.

Conclusions: Tr14 and diclofenac had very different effects on the COX/LOX synthetic pathway after cutaneous wounding. Tr14 allowed normal autoinduction of COX2 mRNA, but suppressed mRNA levels for key enzymes in the leukotriene synthetic pathway. Tr14 appeared to have a broad ‘phytocellular’ effect on the wound transcriptome by altering the balance of cell types present in the wound. Full text of the article available at https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-021-08083-2.

In this competition, co-occuring with the NeurIPS 2021 conference, three problems were presented related to multimodal single cell RNA-seq sequencing data. A first-of-its-kind dataset was compiled to compare participants' solutions.

Participants could choose to solve any of the three problems:

• Given one modality, predict the other. For example, based on the availability of chromatin measured in tens of thousands of cells, one needs to predict RNAexpression for each cell.
• Modality matching. The task is to establish pairwise correspondences between the data of two different modalities, measured in the same cells.
• Representation learning. The task is to reduce the dimension of multimodal data so as to preserve as much as possible information about the biological properties of cells, annotated by experts.

The NOVEL team participated in the first two tasks. Fully connected neural networks were used in the modality prediction task; for the task of modality matching, ideas from the CLIP model developed by OpenAI to match images with their descriptions, were used.The solution to the first problem, proposed by our team, brought victory in the prediction of RNA expression by protein expression subtask. In the match modality task, our team was runner-up in all subtasks. 

Congratulations to our team on the victory!

About the competition: As part of the 35th conference NeurIPS 2021 (Conference on Neural Information Processing Systems), an international competition was announced for solving problems in the field of bioinformatics and applied genomics. 

Organizers and sponsors of the competition: Cellarity, Chan Zuckerberg Initiative and Chan Zuckerberg BIOHUB, Yale University and the Helmholtz Institute (Munich). 

The competition was attended by 276 teams from around the world. The results of the competition are published on the website of the competition and reported at the conference.

A contract for the development of artificial intelligence tools for targeted protein modification was signed with Vector-Best JSC. Thanks to this technology, our client will receive new enzyme proteins with improved properties. This will make it possible to speed up and reduce the cost of production of many products manufactured by Vector-Best JSC .

The developed software based on artificial intelligence algorithms will make it possible to predict the effect of various amino acid substitutions on the target protein. 

Using the developed program, it is possible to select optimal amino acid substitutions to achieve the effect of enhancing specific properties. Our AI algorithms for analyzing proteins form a framework we call Protomenal.

Vector-Best JSC produces more than 600 products for enzyme immunoassay, real-time PCR and clinical biochemistry. The company occupies a leading position in its segment due to its powerful research base - the company includes more than 20 research laboratories, and its own modern facilities- the production of sets is located on thearea of ​​more than 20,000 square meters, a wide network of representative offices and distributors, which allows promptly deliver theproducts to any region of the Russian Federation and CIS.

In September 2021, a regular audit of the workspace of Novel employees in Novosibirsk and St. Petersburg was conducted. Workplace Conditions Assessment (WCA) is a generally accepted industry approach to assessing labor risks. Another test of compliance with the requirements of working conditions, conducted by Intertek Testing Services, showed a 100% result.

In 2019 and 2020 years our company AcademGene LLC and Institute of Information Systems of Siberian Branch of Russian Academy of Sciences worked together on the project «Development of a software complex for automatic modeling of individual implants planes for closing defects of skull bones on the basis of artificial neural networks». Project was co-financed with the Ministry of Science and Innovation Policy of Novosibirsk as AcademGene LLC won the contest of subsidies for innovators.

Objective of the project: Development of a web-based application for analysis of CT data of the skull and automatic selection of the form of the individual implant at the site of damage of the convexity department.
The results of the joint work carried out are as follows