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ФГБОУ ВО "РОССИЙСКИЙ БИОТЕХНОЛОГИЧЕСКИЙ УНИВЕРСИТЕТ (РОСБИОТЕХ)"; РОССИЙСКИЙ БИОТЕХНОЛОГИЧЕСКИЙ УНИВЕРСИТЕТ; ГОСУДАРСТВЕННЫЙ УНИВЕРСИТЕТ РОСБИОТЕХ; ФГБОУ ВО "РОСБИОТЕХ"; УНИВЕР...
Moscow
OGRN: 1037739533699
TIN: 7712029651
Active. Last modified on: June 29, 2023
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2
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OKVED2 85.22 Total: 85
Higher education
Monitoring Notes Reports Contact information
7,32
mln ₽, 2001
Revenue
+₽7mln
Acting as Chancellor
Zhukova Nataliya Viktorovna
100
Reliability Score
JavaScript chart by amCharts 3.21.1
Acting as Chancellor
Zhukova Nataliya Viktorovna
31
years
Established
February 2, 1994
City Moscow
7,32
mln ₽, 2001
Revenue
+₽7mln
549
Connections
+0 last week
Employees
No data

Litigation

Learn more

Stats Over Time

Participation Total number of cases For the last year
Plaintiff
29 cases (▒▒▒▒▒ ₽) 8 cases (▒▒▒▒▒ ₽)
Defendant
54 cases (▒▒▒▒▒ ₽) 2 cases (▒▒▒▒▒ ₽)
Third party
7 cases (▒▒▒▒▒ ₽) 1 case (▒▒▒▒▒ ₽)
Other party
9 cases (▒▒▒▒▒ ₽) 1 case (▒▒▒▒▒ ₽)

Positive outcome — ▒▒%

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Negative outcome — ▒▒%

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JavaScript chart by amCharts 3.21.1

Under consideration — ▒%

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Undefined — ▒▒%

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Type of dispute

%
Administrative
%
Civil
%
Bankruptcy-related
%
Other
×
Claim amount
×
Type of dispute
×
Outcome of case
×

Current cases

As plaintiff (5)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
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As other party (1)
Claims amount: ▒▒▒▒▒ ₽
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Complexity
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Plaintiff
Defendant
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Completed cases

As plaintiff (24)
Claims amount: ▒▒▒▒▒ ₽
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Plaintiff
Defendant
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As defendant (54)
Claims amount: ▒▒▒▒▒ ₽
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Object
Plaintiff
Defendant
Instance
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As third party (7)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount


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As other party (8)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
Claim amount


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Data sources Information about company arbitration cases is collected from public sources.

Accurate binding to a company can be created only if the information source contains its TIN and OGRN values. If identification details are not specified, the binding is created by using linguistic algorithms. Although these algorithms are being constantly improved, some information may be absent.

If you have noticed an error or lack of information, please let us know about it. Let's improve Seldon.Basis together!

Data sources Information about company arbitration cases is collected from public sources.

Accurate binding to a company can be created only if the information source contains its TIN and OGRN values. If identification details are not specified, the binding is created by using linguistic algorithms. Although these algorithms are being constantly improved, some information may be absent.

If you have noticed an error or lack of information, please let us know about it. Let's improve Seldon.Basis together!

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